A
| Abortar | Lanza una excepción para cancelar el proceso cuando se llama. |
| Opciones de cancelación | Atributos opcionales para Abort |
| Abs <T extiende TNumber > | Calcula el valor absoluto de un tensor. |
| Búfer de datos abstractos <T> | |
| AbstractDataBufferWindow <B extiende DataBuffer <?>> | |
| AbstractDenseNdArray <T, U extiende NdArray <T>> | |
| AbstractNdArray <T, U extiende NdArray <T>> | |
| ResumenTF_Buffer | |
| ResumenTF_Graph | |
| ResumenTF_ImportGraphDefOptions | |
| ResumenTF_Session | |
| ResumenTF_SessionOptions | |
| ResumenTF_Estado | |
| ResumenTF_Tensor | |
| ResumenTFE_Context | |
| ResumenTFE_ContextOptions | |
| ResumenTFE_Op | |
| ResumenTFE_TensorHandle | |
| AcumularN <T extiende TType > | Devuelve la suma por elementos de una lista de tensores. |
| AcumuladorAplicarGradiente | Aplica un gradiente a un acumulador determinado. |
| AcumuladorNumAcumulado | Devuelve el número de gradientes agregados en los acumuladores dados. |
| AcumuladorSetGlobalStep | Actualiza el acumulador con un nuevo valor para global_step. |
| AccumulatorTakeGradient <T extiende TType > | Extrae el gradiente promedio en el ConditionalAccumulator dado. |
| Acos <T extiende TType > | Calcula acos de x por elementos. |
| Acosh <T extiende TType > | Calcula el coseno hiperbólico inverso de x por elementos. |
| Activación <T extiende TNumber > | Clase base abstracta para activaciones Nota: El atributo |
| adadelta | Optimizador que implementa el algoritmo Adadelta. |
| adagrad | Optimizador que implementa el algoritmo Adagrad. |
| AdaGradDA | Optimizador que implementa el algoritmo Adagrad Dual-Averaging. |
| Adán | Optimizador que implementa el algoritmo Adam. |
| Adamax | Optimizador que implementa el algoritmo Adamax. |
| Añadir <T extiende TType > | Devuelve x + y por elementos. |
| AgregarManySparseToTensorsMap | Agregue un `N`-minibatch `SparseTensor` a un `SparseTensorsMap`, devuelva `N` identificadores. |
| AddManySparseToTensorsMap.Options | Atributos opcionales para AddManySparseToTensorsMap |
| AgregarN <T extiende TType > | Agregue todos los elementos tensores de entrada. |
| Agregar mapa disperso a tensores | Agregue un `SparseTensor` a un `SparseTensorsMap` y devuelva su identificador. |
| AddSparseToTensorsMap.Options | Atributos opcionales para AddSparseToTensorsMap |
| AjustarContraste <T extiende TNumber > | Ajusta el contraste de una o más imágenes. |
| AjustarHue <T extiende TNumber > | Ajusta el tono de una o más imágenes. |
| AjustarSaturación <T extiende TNumber > | Ajusta la saturación de una o más imágenes. |
| Todo | Calcula el "y lógico" de los elementos en las dimensiones de un tensor. |
| Todas las opciones | Atributos opcionales para All |
| Todos los candidatosSampler | Genera etiquetas para el muestreo de candidatos con una distribución de unigramas aprendida. |
| Todas las opciones de CandidateSampler | Atributos opcionales para AllCandidateSampler |
| Descripción de la asignación | Protobuf tipo tensorflow.AllocationDescription |
| Descripcióndeasignación.Constructor | Protobuf tipo tensorflow.AllocationDescription |
| AsignaciónDescripciónOrConstructor | |
| AsignaciónDescripciónProtos | |
| Registro de asignación | An allocation/de-allocation operation performed by the allocator. |
| Generador de registros de asignación | An allocation/de-allocation operation performed by the allocator. |
| Registro de asignación o constructor | |
| AsignadorMemoriaUsado | Protobuf tipo tensorflow.AllocatorMemoryUsed |
| AllocatorMemoryUsed.Builder | Protobuf tipo tensorflow.AllocatorMemoryUsed |
| AllocatorMemoryUsedOrBuilder | |
| AllReduce <T extiende TNumber > | Reduce mutuamente múltiples tensores de idéntico tipo y forma. |
| Todas las opciones de reducción | Atributos opcionales para AllReduce |
| AllToAll <T extiende TType > | Una operación para intercambiar datos entre réplicas de TPU. |
| Ángulo <U extiende TNumber > | Devuelve el argumento de un número complejo. |
| Iterador anónimo | Un contenedor para un recurso iterador. |
| AnónimoMemoriaCaché | |
| AnónimoMultiDeviceIterator | Un contenedor para un recurso iterador multidispositivo. |
| AnónimoRandomSeedGenerator | |
| Generador de semillas anónimo | |
| Cualquier | Calcula el "o lógico" de elementos en las dimensiones de un tensor. |
| Cualquier.Opciones | Atributos opcionales para Any |
| ApiDef | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Arg | Protobuf tipo tensorflow.ApiDef.Arg |
| ApiDef.Arg.Builder | Protobuf tipo tensorflow.ApiDef.Arg |
| ApiDef.ArgOrBuilder | |
| ApiDef.Attr | Description of the graph-construction-time configuration of this Op. |
| ApiDef.Attr.Builder | Description of the graph-construction-time configuration of this Op. |
| ApiDef.AttrOrBuilder | |
| ApiDef.Constructor | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. |
| ApiDef.Endpoint | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.Endpoint.Builder | If you specify any endpoint, this will replace all of the inherited endpoints. |
| ApiDef.EndpointOrBuilder | |
| ApiDef.Visibilidad | Protobuf enumeración tensorflow.ApiDef.Visibility |
| ApiDefOrBuilder | |
| ApiDefProtos | |
| ApiDefs | Protobuf tipo tensorflow.ApiDefs |
| ApiDefs.Constructor | Protobuf tipo tensorflow.ApiDefs |
| ApiDefsOrBuilder | |
| ApplyAdadelta <T extiende TType > | Actualice '*var' según el esquema adadelta. |
| AplicarAdadelta.Opciones | Atributos opcionales para ApplyAdadelta |
| ApplyAdagrad <T extiende TType > | Actualice '*var' según el esquema adagrad. |
| AplicarAdagrad.Options | Atributos opcionales para ApplyAdagrad |
| ApplyAdagradDa <T extiende TType > | Actualice '*var' según el esquema de adagrad proximal. |
| AplicarAdagradDa.Options | Atributos opcionales para ApplyAdagradDa |
| ApplyAdagradV2 <T extiende TType > | Actualice '*var' según el esquema adagrad. |
| AplicarAdagradV2.Opciones | Atributos opcionales para ApplyAdagradV2 |
| ApplyAdam <T extiende TType > | Actualice '*var' según el algoritmo de Adam. |
| AplicarAdam.Opciones | Atributos opcionales para ApplyAdam |
| ApplyAdaMax <T extiende TType > | Actualice '*var' según el algoritmo AdamMax. |
| AplicarAdaMax.Opciones | Atributos opcionales para ApplyAdaMax |
| ApplyAddSign <T extiende TType > | Actualice '*var' según la actualización de AddSign. |
| AplicarAddSign.Options | Atributos opcionales para ApplyAddSign |
| ApplyCenteredRmsProp <T extiende TType > | Actualice '*var' según el algoritmo RMSProp centrado. |
| AplicarCenteredRmsProp.Options | Atributos opcionales para ApplyCenteredRmsProp |
| ApplyFtrl <T extiende TType > | Actualice '*var' según el esquema Ftrl-proximal. |
| AplicarFtrl.Opciones | Atributos opcionales para ApplyFtrl |
| ApplyGradientDescent <T extiende TType > | Actualice '*var' restándole 'alfa' * 'delta'. |
| AplicarGradientDescent.Opciones | Atributos opcionales para ApplyGradientDescent |
| ApplyMomentum <T extiende TType > | Actualice '*var' según el esquema de impulso. |
| AplicarMomentum.Opciones | Atributos opcionales para ApplyMomentum |
| ApplyPowerSign <T extiende TType > | Actualice '*var' según la actualización de AddSign. |
| AplicarPowerSign.Opciones | Atributos opcionales para ApplyPowerSign |
| ApplyProximalAdagrad <T extiende TType > | Actualice '*var' y '*accum' según FOBOS con la tasa de aprendizaje de Adagrad. |
| AplicarProximalAdagrad.Options | Atributos opcionales para ApplyProximalAdagrad |
| ApplyProximalGradientDescent <T extiende TType > | Actualice '*var' como algoritmo FOBOS con tasa de aprendizaje fija. |
| AplicarProximalGradientDescent.Options | Atributos opcionales para ApplyProximalGradientDescent |
| ApplyRmsProp <T extiende TType > | Actualice '*var' según el algoritmo RMSProp. |
| AplicarRmsProp.Opciones | Atributos opcionales para ApplyRmsProp |
| AproximadamenteIgual | Devuelve el valor de verdad de abs(xy) <tolerancia por elementos. |
| Opciones iguales aproximadas | Atributos opcionales para ApproximateEqual |
| ArgMax <V extiende TNumber > | Devuelve el índice con el valor más grande en todas las dimensiones de un tensor. |
| ArgMin <V extiende TNumber > | Devuelve el índice con el valor más pequeño entre las dimensiones de un tensor. |
| Asin <T extiende TType > | Calcula el seno inverso trigonométrico de x por elementos. |
| Asinh <T extiende TType > | Calcula el seno hiperbólico inverso de x por elementos. |
| Afirmar cardinalidadConjunto de datos | |
| Afirmar el siguiente conjunto de datos | Una transformación que afirma qué transformaciones ocurren a continuación. |
| Afirmar el siguiente conjunto de datos | |
| Afirmar que | Afirma que la condición dada es verdadera. |
| Afirmar eso. Opciones | Atributos opcionales para AssertThat |
| AssetFileDef | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDef.Builder | An asset file def for a single file or a set of sharded files with the same name. |
| AssetFileDefOrBuilder | |
| Asignar <T extiende TType > | Actualice 'ref' asignándole 'valor'. |
| Asignar opciones | Atributos opcionales para Assign |
| AsignarAgregar <T extiende TType > | Actualice 'ref' agregándole 'valor'. |
| Asignar opciones adicionales | Atributos opcionales para AssignAdd |
| AsignarAgregarVariableOp | Agrega un valor al valor actual de una variable. |
| AssignSub <T extiende TType > | Actualice 'ref' restándole 'valor'. |
| AsignarSub.Opciones | Atributos opcionales para AssignSub |
| AsignarSubVariableOp | Resta un valor del valor actual de una variable. |
| AsignarVariableOp | Asigna un nuevo valor a una variable. |
| Como cadena | Convierte cada entrada del tensor dado en cadenas. |
| AsString.Opciones | Atributos opcionales para AsString |
| Atan <T extiende TType > | Calcula la tangente inversa trigonométrica de x por elementos. |
| Atan2 <T extiende TNumber > | Calcula la arcotangente de `y/x` por elementos, respetando los signos de los argumentos. |
| Atanh <T extiende TType > | Calcula la tangente hiperbólica inversa de x por elementos. |
| ValorAtributo | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.Constructor | Protocol buffer representing the value for an attr used to configure an Op. |
| AttrValue.ListValue | LINT.IfChangeProtobuf tipo tensorflow.AttrValue.ListValue |
| AttrValue.ListValue.Builder | LINT.IfChangeProtobuf tipo tensorflow.AttrValue.ListValue |
| AttrValue.ListValueOrBuilder | |
| AttrValue.ValueCase | |
| AttrValueOrBuilder | |
| AttrValueProtos | |
| Audioespectrograma | Produce una visualización de datos de audio a lo largo del tiempo. |
| AudioEspectrograma.Opciones | Atributos opcionales para AudioSpectrogram |
| AudioResumen | Genera un búfer de protocolo "Resumen" con audio. |
| AudioResumen.Opciones | Atributos opcionales para AudioSummary |
| Opciones de AutoParalelo | Protobuf tipo tensorflow.AutoParallelOptions |
| AutoParallelOptions.Builder | Protobuf tipo tensorflow.AutoParallelOptions |
| AutoParallelOptionsOrBuilder | |
| Conjunto de datos AutoShard | Crea un conjunto de datos que fragmenta el conjunto de datos de entrada. |
| Conjunto de datos AutoShard | Crea un conjunto de datos que fragmenta el conjunto de datos de entrada. |
| AutoShardDataset.Opciones | Atributos opcionales para AutoShardDataset |
| AutoShardDataset.Opciones | Atributos opcionales para AutoShardDataset |
| DisponibleInformación del dispositivo | Matches DeviceAttributesProtobuf tipo tensorflow.AvailableDeviceInfo |
| DisponibleDeviceInfo.Builder | Matches DeviceAttributesProtobuf tipo tensorflow.AvailableDeviceInfo |
| DisponibleDeviceInfoOrBuilder | |
| AvgPool <T extiende TNumber > | Realiza una agrupación promedio en la entrada. |
| AvgPool.Opciones | Atributos opcionales para AvgPool |
| AvgPool3d <T extiende TNumber > | Realiza una agrupación promedio 3D en la entrada. |
| AvgPool3d.Opciones | Atributos opcionales para AvgPool3d |
| AvgPool3dGrad <T extiende TNumber > | Calcula los gradientes de la función de agrupación promedio. |
| AvgPool3dGrad.Options | Atributos opcionales para AvgPool3dGrad |
| AvgPoolGrad <T extiende TNumber > | Calcula los gradientes de la función de agrupación promedio. |
| Opciones AvgPoolGrad. | Atributos opcionales para AvgPoolGrad |
B
| BandedTriangularSolve <T extiende TType > | |
| Opciones de solución triangular con bandas | Atributos opcionales para BandedTriangularSolve |
| BandPart <T extiende TType > | Copie un tensor poniendo a cero todo lo que está fuera de una banda central en cada matriz más interna. |
| Barrera | Define una barrera que persiste en diferentes ejecuciones de gráficos. |
| Barrera.Opciones | Atributos opcionales para Barrier |
| BarreraCerrar | Cierra la barrera dada. |
| BarreraCerrar.Opciones | Atributos opcionales para BarrierClose |
| BarreraIncompletaTamaño | Calcula el número de elementos incompletos en la barrera dada. |
| BarreraInsertarMuchos | Para cada clave, asigna el valor respectivo al componente especificado. |
| BarreraListoTamaño | Calcula el número de elementos completos en la barrera dada. |
| barreratomarmuchos | Toma el número dado de elementos completos de una barrera. |
| BarreraTomaMuchas.Opciones | Atributos opcionales para BarrierTakeMany |
| BaseInitializer <T extiende TType > | Clase base abstracta para todos los inicializadores |
| Lote | Agrupa todos los tensores de entrada por lotes de forma no determinista. |
| Opciones.de.lote | Atributos opcionales para Batch |
| BatchCholesky <T extiende TNumber > | |
| BatchCholeskyGrad <T extiende TNumber > | |
| Conjunto de datos por lotes | |
| Conjunto de datos por lotes | Crea un conjunto de datos que agrupa elementos `batch_size` desde `input_dataset`. |
| Opciones de conjunto de datos por lotes | Atributos opcionales para BatchDataset |
| LoteFft | |
| LoteFft2d | |
| LoteFft3d | |
| loteIfft | |
| loteIfft2d | |
| loteIfft3d | |
| BatchMatMul <T extiende TType > | Multiplica porciones de dos tensores en lotes. |
| Opciones de BatchMatMul | Atributos opcionales para BatchMatMul |
| BatchMatrixBandPart <T extiende TType > | |
| BatchMatrixDeterminant <T extiende TType > | |
| BatchMatrixDiag <T extiende TType > | |
| BatchMatrixDiagPart <T extiende TType > | |
| BatchMatrixInverse <T extiende TNumber > | |
| BatchMatrixInverse.Opciones | Atributos opcionales para BatchMatrixInverse |
| BatchMatrixSetDiag <T extiende TType > | |
| BatchMatrixSolve <T extiende TNumber > | |
| BatchMatrixSolve.Opciones | Atributos opcionales para BatchMatrixSolve |
| BatchMatrixSolveLs <T extiende TNumber > | |
| BatchMatrixSolveLs.Opciones | Atributos opcionales para BatchMatrixSolveLs |
| BatchMatrixTriangularSolve <T extiende TNumber > | |
| BatchMatrixTriangularSolve.Opciones | Atributos opcionales para BatchMatrixTriangularSolve |
| BatchNormWithGlobalNormalization <T extiende TType > | Normalización por lotes. |
| BatchNormWithGlobalNormalizationGrad <T extiende TType > | Gradientes para normalización por lotes. |
| BatchSelfAdjointEig <T extiende TNumber > | |
| BatchSelfAdjointEig.Opciones | Atributos opcionales para BatchSelfAdjointEig |
| BatchSvd <T extiende TType > | |
| Opciones de BatchSvd | Atributos opcionales para BatchSvd |
| BatchToSpace <T extiende TType > | BatchToSpace para tensores 4-D de tipo T. |
| BatchToSpaceNd <T extiende TType > | BatchToSpace para tensores ND de tipo T. |
| Entradas de referencia | tensorflow.BenchmarkEntries tipo protobuf.BenchmarkEntries |
| BenchmarkEntries.Builder | tensorflow.BenchmarkEntries tipo protobuf.BenchmarkEntries |
| BenchmarkEntriesOrBuilder | |
| Entrada de referencia | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntry.Builder | Each unit test or benchmark in a test or benchmark run provides some set of information. |
| BenchmarkEntryOrBuilder | |
| BesselI0 <T extiende TNumber > | |
| BesselI0e <T extiende TNumber > | |
| BesselI1 <T extiende TNumber > | |
| BesselI1e <T extiende TNumber > | |
| BesselJ0 <T extiende TNumber > | |
| BesselJ1 <T extiende TNumber > | |
| BesselK0 <T extiende TNumber > | |
| BesselK0e <T extiende TNumber > | |
| BesselK1 <T extiende TNumber > | |
| BesselK1e <T extiende TNumber > | |
| BesselY0 <T extiende TNumber > | |
| BesselY1 <T extiende TNumber > | |
| Betainc <T extiende TNumber > | Calcular la integral beta incompleta regularizada \\(I_x(a, b)\\). |
| BfcMemoryMapProtos | |
| Bfloat16Diseño | Diseño de datos que convierte flotantes de 32 bits de/a 16 bits, truncando su mantisa a 7 bits pero preservando el exponente de 8 bits con el mismo sesgo. |
| BiasAdd <T extiende TType > | Agrega "sesgo" al "valor". |
| BiasAdd.Opciones | Atributos opcionales para BiasAdd |
| BiasAddGrad <T extiende TType > | La operación hacia atrás para "BiasAdd" en el tensor de "sesgo". |
| BiasAddGrad.Opciones | Atributos opcionales para BiasAddGrad |
| Cruzentropía binaria | Calcula la pérdida de entropía cruzada entre etiquetas verdaderas y etiquetas predichas. |
| BinaryCrossentropy <T extiende TNumber > | Métrica que calcula la pérdida de entropía cruzada binaria entre etiquetas verdaderas y etiquetas previstas. |
| Bincount <T extiende TNumber > | Cuenta el número de apariciones de cada valor en una matriz de números enteros. |
| BinResumen | tensorflow.BinSummary tipo Protobuf.BinSummary |
| BinSummary.Builder | tensorflow.BinSummary tipo Protobuf.BinSummary |
| BinResumenOrBuilder | |
| Bitcast <U extiende TType > | Transmite un tensor de un tipo a otro sin copiar datos. |
| Bit a bitY <T extiende TNumber > | Elementwise calcula el AND bit a bit de `x` e `y`. |
| Bit a bitO <T extiende TNumber > | Elementwise calcula el OR bit a bit de `x` e `y`. |
| BitwiseXor <T extiende TNumber > | Elementwise calcula el XOR bit a bit de `x` e `y`. |
| BlockLSTM <T extiende TNumber > | Calcula la propagación directa de la celda LSTM para todos los pasos de tiempo. |
| BlockLSTM.Opciones | Atributos opcionales para BlockLSTM |
| BlockLSTMGrad <T extiende TNumber > | Calcula la propagación hacia atrás de la celda LSTM para toda la secuencia de tiempo. |
| Búfer de datos booleanos | Un DataBuffer de valores booleanos. |
| BooleanDataLayout <S extiende DataBuffer <?>> | Un DataLayout que convierte los datos almacenados en un búfer a booleanos. |
| BooleanoDensoNdArray | |
| Máscara booleana | |
| Opciones de máscara booleana | Atributos opcionales para BooleanMask |
| Actualización de máscara booleana | |
| Opciones de actualización de máscara booleana | Atributos opcionales para BooleanMaskUpdate |
| BooleanoNdArray | Un NdArray de booleanos. |
| Diseño bool | Diseño de datos que convierte valores booleanos de/a bytes. |
| Árboles impulsadosEstadísticas agregadas | Agrega el resumen de estadísticas acumuladas para el lote. |
| ImpulsadoárbolesBucketize | Divida cada característica en grupos según los límites del grupo. |
| ImpulsadoÁrbolesCalcularMejorCaracterísticaDividir | Calcula las ganancias de cada función y devuelve la mejor información dividida posible para la función. |
| BoostedTreesCalculateBestFeatureSplit.Options | Atributos opcionales para BoostedTreesCalculateBestFeatureSplit |
| ImpulsadoÁrbolesCalcularMejorCaracterísticaSplitV2 | Calcula las ganancias para cada característica y devuelve la mejor información dividida posible para cada nodo. |
| Árboles impulsadosCalcularmejoresgananciasporcaracterística | Calcula las ganancias de cada función y devuelve la mejor información dividida posible para la función. |
| Árboles impulsadosCentroBias | Calcula el prior a partir de los datos de entrenamiento (el sesgo) y completa el primer nodo con el prior de los logits. |
| Árboles impulsadosCrear conjunto | Crea un modelo de conjunto de árboles y le devuelve un identificador. |
| BoostedTreesCreateQuantileStreamResource | Cree el recurso para secuencias cuantiles. |
| BoostedTreesCreateQuantileStreamResource.Options | Atributos opcionales para BoostedTreesCreateQuantileStreamResource |
| Árboles impulsadosDeserializeEnsemble | Deserializa una configuración de conjunto de árbol serializado y reemplaza el árbol actual conjunto. |
| ImpulsadoTreesEnsembleResourceHandleOp | Crea un identificador para BoostedTreesEnsembleResource |
| BoostedTreesEnsembleResourceHandleOp.Options | Atributos opcionales para BoostedTreesEnsembleResourceHandleOp |
| BoostedTreesEjemploDebugOutputs | Resultados de depuración/interpretabilidad del modelo para cada ejemplo. |
| ImpulsadoÁrbolesFlushCuantilResúmenes | Elimine los resúmenes cuantiles de cada recurso de flujo cuantil. |
| Árboles impulsadosGetEnsembleStates | Recupera el token de sello de recursos del conjunto de árboles, la cantidad de árboles y las estadísticas de crecimiento. |
| ImpulsadoTreesMakeQuantileResúmenes | Realiza el resumen de cuantiles del lote. |
| BoostedTreesMakeStatsResumen | Realiza el resumen de estadísticas acumuladas del lote. |
| Árboles impulsadosPredecir | Ejecuta múltiples predictores de conjuntos de regresión aditiva en instancias de entrada y calcula los logits. |
| BoostedTreesQuantileStreamResourceAgregarResúmenes | Agregue los resúmenes cuantiles a cada recurso de flujo cuantil. |
| BoostedTreesQuantileStreamResourceDeserialize | Deserialice los límites del depósito y el indicador listo en el QuantileAccumulator actual. |
| ImpulsadoTreesQuantileStreamResourceFlush | Vacíe los resúmenes de un recurso de flujo cuantil. |
| BoostedTreesQuantileStreamResourceFlush.Options | Atributos opcionales para BoostedTreesQuantileStreamResourceFlush |
| BoostedTreesQuantileStreamResourceGetBucketBoundaries | Genere los límites del depósito para cada característica en función de los resúmenes acumulados. |
| ImpulsadoTreesQuantileStreamResourceHandleOp | Crea un identificador para BoostedTreesQuantileStreamResource. |
| BoostedTreesQuantileStreamResourceHandleOp.Options | Atributos opcionales para BoostedTreesQuantileStreamResourceHandleOp |
| ImpulsadoTreesSerializeEnsemble | Serializa el conjunto de árboles en un proto. |
| BoostedTreesSparseAggregateStats | Agrega el resumen de estadísticas acumuladas para el lote. |
| ImpulsadoÁrbolesEscasoCalcularMejorCaracterísticaDividir | Calcula las ganancias de cada función y devuelve la mejor información dividida posible para la función. |
| BoostedTreesSparseCalculateBestFeatureSplit.Options | Atributos opcionales para BoostedTreesSparseCalculateBestFeatureSplit |
| ImpulsadoÁrbolesEntrenamientoPredecir | Ejecuta múltiples predictores de conjuntos de regresión aditiva en instancias de entrada y calcula la actualización de los logits almacenados en caché. |
| Conjunto de actualización de árboles impulsados | Actualiza el conjunto de árboles agregando una capa al último árbol que se está cultivando o iniciando un nuevo árbol. |
| ImpulsadoTreesUpdateEnsembleV2 | Actualiza el conjunto de árboles agregando una capa al último árbol que se está cultivando. o iniciando un nuevo árbol. |
| BoostedTreesUpdateEnsembleV2.Opciones | Atributos opcionales para BoostedTreesUpdateEnsembleV2 |
| BoundedTensorSpecProto | A protobuf to represent tf.BoundedTensorSpec. |
| BoundedTensorSpecProto.Builder | A protobuf to represent tf.BoundedTensorSpec. |
| LimitadoTensorSpecProtoOrBuilder | |
| BroadcastDynamicShape <T extiende TNumber > | Devuelve la forma de s0 op s1 con transmisión. |
| BroadcastGradientArgs <T extiende TNumber > | Devuelve los índices de reducción para calcular gradientes de s0 op s1 con transmisión. |
| BroadcastHelper <T extiende TType > | Operador auxiliar para realizar transmisiones estilo XLA Transmite `lhs` y `rhs` con el mismo rango, agregando dimensiones de tamaño 1 a cualquiera de los `lhs` y `rhs` que tenga el rango inferior, utilizando las reglas de transmisión de XLA para operadores binarios. |
| BroadcastRecv <T extiende TType > | Recibe un valor tensor transmitido desde otro dispositivo. |
| Opciones de recepción de transmisión | Atributos opcionales para BroadcastRecv |
| BroadcastSend <T extiende TType > | Transmite un valor de tensor a uno o más dispositivos. |
| Opciones de envío de transmisión | Atributos opcionales para BroadcastSend |
| BroadcastTo <T extiende TType > | Transmita una matriz para obtener una forma compatible. |
| Bucketizar | Divide las 'entradas' en función de los 'límites'. |
| Configuración de compilación | tensorflow.BuildConfiguration tipo protobuf.BuildConfiguration |
| BuildConfiguration.Builder | tensorflow.BuildConfiguration tipo protobuf.BuildConfiguration |
| BuildConfigurationOrBuilder | |
| BundleEntryProto | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProto.Builder | Describes the metadata related to a checkpointed tensor. |
| BundleEntryProtoOrBuilder | |
| PaqueteHeaderProto | Special header that is associated with a bundle. |
| PaqueteHeaderProto.Builder | Special header that is associated with a bundle. |
| BundleHeaderProto.Endianness | An enum indicating the endianness of the platform that produced this bundle. |
| PaqueteHeaderProtoOrBuilder | |
| Búfer de datos de bytes | Un DataBuffer de bytes. |
| ByteDataLayout <S extiende DataBuffer <?>> | Un DataLayout que convierte los datos almacenados en un búfer en bytes. |
| ByteDenseNdArray | |
| ByteNdArray | Un NdArray de bytes. |
| Proveedor de secuencia de bytes <T> | Produce una secuencia de bytes que se almacenarán en un ByteSequenceTensorBuffer . |
| ByteSecuenciaTensorBuffer | Búfer para almacenar datos del tensor de cuerdas. |
| Lista de bytes | Containers to hold repeated fundamental values. |
| BytesList.Builder | Containers to hold repeated fundamental values. |
| BytesListOrBuilder | |
| BytesProducidoEstadísticasConjunto de datos | Registra el tamaño de bytes de cada elemento de `input_dataset` en un StatsAggregator. |
| BytesProducidoEstadísticasConjunto de datos | Registra el tamaño de bytes de cada elemento de `input_dataset` en un StatsAggregator. |
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| Conjunto de datos de caché | Crea un conjunto de datos que almacena en caché elementos de `input_dataset`. |
| CachéDatasetV2 | |
| Opciones invocables | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| Opciones invocables.Builder | Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed. |
| Opciones invocables o constructor | |
| Cast <U extiende TType > | Transfiera x de tipo SrcT a y de DstT. |
| Opciones de transmisión | Atributos opcionales para Cast |
| Ayudante del reparto | Una clase de ayuda para emitir un operando |
| CategóricoCrossentropía | Calcula la pérdida de entropía cruzada entre las etiquetas y las predicciones. |
| CategoricalCrossentropy <T extiende TNumber > | Métrica que calcula la pérdida de entropía cruzada categórica entre etiquetas verdaderas y etiquetas previstas. |
| Bisagra categórica | Calcula la pérdida de bisagra categórica entre etiquetas y predicciones. |
| Bisagra categórica <T extiende TNumber > | Métrica que calcula la métrica de pérdida de bisagra categórica entre etiquetas y predicciones. |
| Ceil <T extiende TNumber > | Devuelve el entero más pequeño por elementos no menor que x. |
| CheckNumerics <T extiende TNumber > | Comprueba un tensor en busca de valores NaN, -Inf y +Inf. |
| Cholesky <T extiende TType > | Calcula la descomposición de Cholesky de una o más matrices cuadradas. |
| CholeskyGrad <T extiende TNumber > | Calcula el gradiente retropropagado en modo inverso del algoritmo de Cholesky. |
| Elija el conjunto de datos más rápido | |
| Elija el conjunto de datos más rápido | |
| ClipByValue <T extiende TType > | Recorta los valores del tensor a un mínimo y un máximo especificados. |
| CerrarResumenEscritor | |
| Definición de clúster | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDef.Constructor | Defines a TensorFlow cluster as a set of jobs. |
| ClusterDefOrBuilder | |
| Filtros de dispositivos de clúster | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFilters.Builder | Defines the device filters for jobs in a cluster. |
| ClusterDeviceFiltersOrBuilder | |
| Salida de clúster <T extiende TType > | Operador que conecta la salida de un cálculo XLA a otros nodos del gráfico de consumo. |
| ClústerProtos | |
| Código | The canonical error codes for TensorFlow APIs. |
| CódigoUbicación | Code location information: A stack trace with host-name information. |
| CódigoUbicación.Constructor | Code location information: A stack trace with host-name information. |
| CódigoUbicaciónOrConstructor | |
| ColecciónDef | CollectionDef should cover most collections. |
| ColecciónDef.AnyList | AnyList is used for collecting Any protos. |
| ColecciónDef.AnyList.Builder | AnyList is used for collecting Any protos. |
| ColecciónDef.AnyListOrBuilder | |
| ColecciónDef.Builder | CollectionDef should cover most collections. |
| ColecciónDef.BytesList | BytesList is used for collecting strings and serialized protobufs. |
| ColecciónDef.BytesList.Builder | BytesList is used for collecting strings and serialized protobufs. |
| ColecciónDef.BytesListOrBuilder | |
| ColecciónDef.FloatList | FloatList is used for collecting float values. |
| ColecciónDef.FloatList.Builder | FloatList is used for collecting float values. |
| ColecciónDef.FloatListOrBuilder | |
| ColecciónDef.Int64List | Int64List is used for collecting int, int64 and long values. |
| ColecciónDef.Int64List.Builder | Int64List is used for collecting int, int64 and long values. |
| ColecciónDef.Int64ListOrBuilder | |
| ColecciónDef.KindCase | |
| ColecciónDef.NodeList | NodeList is used for collecting nodes in graph. |
| ColecciónDef.NodeList.Builder | NodeList is used for collecting nodes in graph. |
| ColecciónDef.NodeListOrBuilder | |
| ColecciónDefOrBuilder | |
| CollectiveGather <T extiende TNumber > | Acumula mutuamente múltiples tensores de idéntico tipo y forma. |
| Opciones de recopilación colectiva | Atributos opcionales para CollectiveGather |
| CollectivePermute <T extiende TType > | Una operación para permutar tensores entre instancias de TPU replicadas. |
| Supresión combinada no máxima | Selecciona con avidez un subconjunto de cuadros delimitadores en orden descendente de puntuación, Esta operación realiza non_max_suppression en las entradas por lote, en todas las clases. |
| Opciones combinadas de NonMaxSuppression | Atributos opcionales para CombinedNonMaxSuppression |
| Id. de confirmación | Protobuf tipo tensorflow.CommitId |
| ConfirmarId.Builder | Protobuf tipo tensorflow.CommitId |
| ConfirmarId.KindCase | |
| ConfirmarIdOrBuilder | |
| Comparar y Bitpack | Compare los valores de "entrada" con el "umbral" y empaquete los bits resultantes en un "uint8". |
| Resultado de compilación | Devuelve el resultado de una compilación de TPU. |
| CompileSucceededAssert | Afirma que la compilación fue exitosa. |
| Complejo <U extiende TType > | Convierte dos números reales en un número complejo. |
| ComplexAbs <U extiende TNumber > | Calcula el valor absoluto complejo de un tensor. |
| ComprimirElemento | Comprime un elemento del conjunto de datos. |
| Compute_func_Pointer_TF_OpKernelContext | |
| ComputarGolpes Accidentales | Calcula los identificadores de las posiciones en sampled_candidates que coinciden con true_labels. |
| ComputeAccidentalHits.Options | Atributos opcionales para ComputeAccidentalHits |
| Calcular tamaño de lote | Calcula el tamaño de lote estático de un conjunto de datos sin lotes parciales. |
| Concat <T extiende TType > | Concatena tensores a lo largo de una dimensión. |
| Concatenar conjunto de datos | Crea un conjunto de datos que concatena `input_dataset` con `another_dataset`. |
| Función Concreta | Un gráfico que se puede invocar como una función única, con una firma de entrada y salida. |
| CondContextDef | Protocol buffer representing a CondContext object. |
| CondContextDef.Builder | Protocol buffer representing a CondContext object. |
| CondContextDefOrBuilder | |
| Acumulador condicional | Un acumulador condicional para agregar gradientes. |
| Opciones de acumulador condicional | Atributos opcionales para ConditionalAccumulator |
| Proto de configuración | Session configuration parameters. |
| ConfigProto.Builder | Session configuration parameters. |
| ConfigProto.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| ConfigProto.Experimental.MlirBridgeRollout | An enum that describes the state of the MLIR bridge rollout. |
| ConfigProto.ExperimentalOrBuilder | |
| ConfigProtoOrBuilder | |
| Protos de configuración | |
| Configurar TPU distribuido | Configura las estructuras centralizadas para un sistema TPU distribuido. |
| Configurar opciones de TPU distribuidas | Atributos opcionales para ConfigureDistributedTPU |
| ConfigurarTPUEmbedding | Configura TPUEmbedding en un sistema TPU distribuido. |
| Conj <T extiende TType > | Devuelve el conjugado complejo de un número complejo. |
| ConjugateTranspose <T extiende TType > | Mezcla las dimensiones de x según una permutación y conjuga el resultado. |
| Constante <T extiende TType > | Inicializador que genera tensores con un valor constante. |
| Constante <T extiende TType > | Un operador que produce un valor constante. |
| Restricción | Clase base para restricciones. |
| ConsumirMutexBloquear | Esta operación consume un bloqueo creado por "MutexLock". |
| ControlFlowContextDef | Container for any kind of control flow context. |
| ControlFlowContextDef.Builder | Container for any kind of control flow context. |
| ControlFlowContextDef.CtxtCase | |
| ControlFlowContextDefOrBuilder | |
| ControlFlowProtos | |
| ControlDisparador | No hace nada. |
| Conv <T extiende TType > | Envuelve el operador XLA ConvGeneralDilated, documentado en https://www.tensorflow.org/rendimiento/xla/operación_semantics#conv_convolution. |
| Conv2d <T extiende TNumber > | Calcula una convolución 2-D dados los tensores de "entrada" y "filtro" 4-D. |
| Opciones de conversión 2d | Atributos opcionales para Conv2d |
| Conv2dBackpropFilter <T extiende TNumber > | Calcula los gradientes de convolución con respecto al filtro. |
| Conv2dBackpropFilter.Opciones | Atributos opcionales para Conv2dBackpropFilter |
| Conv2dBackpropInput <T extiende TNumber > | Calcula los gradientes de convolución con respecto a la entrada. |
| Conv2dBackpropInput.Opciones | Atributos opcionales para Conv2dBackpropInput |
| Conv3d <T extiende TNumber > | Calcula una convolución 3D dados los tensores de "entrada" y "filtro" 5D. |
| Opciones de conversión 3d | Atributos opcionales para Conv3d |
| Conv3dBackpropFilter <T extiende TNumber > | Calcula los gradientes de convolución 3-D con respecto al filtro. |
| Conv3dBackpropFilter.Opciones | Atributos opcionales para Conv3dBackpropFilter |
| Conv3dBackpropInput <U extiende TNumber > | Calcula los gradientes de convolución 3-D con respecto a la entrada. |
| Conv3dBackpropInput.Opciones | Atributos opcionales para Conv3dBackpropInput |
| Copiar <T extiende TType > | Copie un tensor de CPU a CPU o de GPU a GPU. |
| Copiar.Opciones | Atributos opcionales para Copy |
| CopyHost <T extiende TType > | Copia un tensor al host. |
| Opciones de CopyHost | Atributos opcionales para CopyHost |
| Porque <T extiende TType > | Calcula el cos de x por elementos. |
| Cosh <T extiende TType > | Calcula el coseno hiperbólico de x por elementos. |
| CosenoSimilitud | Calcula la similitud del coseno entre etiquetas y predicciones. |
| CosenoSimilaridad <T extiende TNumber > | Métrica que calcula la métrica de similitud del coseno entre etiquetas y predicciones. |
| CostoGráficoDef | Protobuf tipo tensorflow.CostGraphDef |
| CostGraphDef.AggregatedCost | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCost.Builder | Total cost of this graph, typically used for balancing decisions. |
| CostGraphDef.AggregatedCostOrBuilder | |
| CostGraphDef.Builder | Protobuf tipo tensorflow.CostGraphDef |
| CostGraphDef.Nodo | Protobuf tipo tensorflow.CostGraphDef.Node |
| CostGraphDef.Node.Builder | Protobuf tipo tensorflow.CostGraphDef.Node |
| CostGraphDef.Node.InputInfo | Inputs of this node. |
| CostGraphDef.Node.InputInfo.Builder | Inputs of this node. |
| CostGraphDef.Node.InputInfoOrBuilder | |
| CostGraphDef.Node.OutputInfo | Outputs of this node. |
| CostGraphDef.Node.OutputInfo.Builder | Outputs of this node. |
| CostGraphDef.Node.OutputInfoOrBuilder | |
| CostGraphDef.NodeOrBuilder | |
| CostGraphDefOrBuilder | |
| CostGraphProtos | |
| CountUpTo <T extiende TNumber > | Incrementa 'ref' hasta que alcanza el 'límite'. |
| Información de CPU | Protobuf tipo tensorflow.CPUInfo |
| CPUInfo.Constructor | Protobuf tipo tensorflow.CPUInfo |
| CPUInfoOrBuilder | |
| Create_func_TF_OpKernelConstruction | |
| CrearResumenDbWriter | |
| CrearResumenFileWriter | |
| Recortar y cambiar tamaño | Extrae cultivos del tensor de imagen de entrada y les cambia el tamaño. |
| Opciones de recorte y cambio de tamaño | Atributos opcionales para CropAndResize |
| CropAndResizeGradBoxes | Calcula el gradiente de crop_and_resize op con el tensor de cuadros de entrada. |
| CropAndResizeGradBoxes.Opciones | Atributos opcionales para CropAndResizeGradBoxes |
| CropAndResizeGradImage <T extiende TNumber > | Calcula el gradiente de la operación crop_and_resize con el tensor de la imagen de entrada. |
| CropAndResizeGradImage.Opciones | Atributos opcionales para CropAndResizeGradImage |
| Cruz <T extiende TNumber > | Calcule el producto cruzado por pares. |
| CrossReplicaSum <T extiende TNumber > | Una operación para sumar entradas entre instancias de TPU replicadas. |
| CSRSparseMatrixComponents <T extiende TType > | Lee en voz alta los componentes de CSR en el "índice" del lote. |
| CSRSparseMatrixToDense <T extiende TType > | Convierta un CSRSparseMatrix (posiblemente por lotes) en denso. |
| CSRSparseMatrixToSparseTensor <T extiende TType > | Convierte un CSRSparesMatrix (posiblemente por lotes) en un SparseTensor. |
| Conjunto de datos CSV | |
| Conjunto de datos CSV | |
| CSVDatasetV2 | |
| CtcBeamSearchDecoder <T extiende TNumber > | Realiza decodificación de búsqueda de haz en los logits dados en la entrada. |
| CtcBeamSearchDecoder.Opciones | Atributos opcionales para CtcBeamSearchDecoder |
| CtcGreedyDecoder <T extiende TNumber > | Realiza una decodificación codiciosa en los logits dados en las entradas. |
| CtcGreedyDecoder.Opciones | Atributos opcionales para CtcGreedyDecoder |
| CtcLoss <T extiende TNumber > | Calcula la pérdida de CTC (probabilidad logarítmica) para cada entrada de lote. |
| CtcLoss.Opciones | Atributos opcionales para CtcLoss |
| CTCLossV2 | Calcula la pérdida de CTC (probabilidad logarítmica) para cada entrada de lote. |
| CTCLossV2.Opciones | Atributos opcionales para CTCLossV2 |
| CudnnRNN <T extiende TNumber > | Un RNN respaldado por cuDNN. |
| CudnnRNN.Opciones | Atributos opcionales para CudnnRNN |
| CudnnRNNBackprop <T extiende TNumber > | Paso de respaldo de CudnnRNNV3. |
| CudnnRNNBackprop.Opciones | Atributos opcionales para CudnnRNNBackprop |
| CudnnRNNCanonicalToParams <T extiende TNumber > | Convierte los parámetros CudnnRNN de forma canónica a forma utilizable. |
| CudnnRNNCanonicalToParams.Options | Atributos opcionales para CudnnRNNCanonicalToParams |
| CudnnRnnParamsSize <U extiende TNumber > | Calcula el tamaño de los pesos que puede utilizar un modelo Cudnn RNN. |
| CudnnRnnParamsSize.Options | Atributos opcionales para CudnnRnnParamsSize |
| CudnnRNNParamsToCanonical <T extiende TNumber > | Recupera los parámetros de CudnnRNN en forma canónica. |
| CudnnRNNParamsToCanonical.Options | Atributos opcionales para CudnnRNNParamsToCanonical |
| Cumprod <T extiende TType > | Calcule el producto acumulativo del tensor "x" a lo largo del "eje". |
| Cumprod.Opciones | Atributos opcionales para Cumprod |
| Cumsum <T extiende TType > | Calcule la suma acumulada del tensor "x" a lo largo del "eje". |
| Cumsum.Opciones | Atributos opcionales para Cumsum |
| CumulativeLogsumexp <T extiende TNumber > | Calcule el producto acumulativo del tensor "x" a lo largo del "eje". |
| Opciones acumulativas de Logsumexp. | Atributos opcionales para CumulativeLogsumexp |
D
| Búfer de datos <T> | Un contenedor de datos de un tipo específico. |
| Fábrica de adaptadores de búfer de datos | Fábrica de adaptadores de buffer de datos. |
| Búfers de datos | Clase auxiliar para crear instancias DataBuffer . |
| DataBufferWindow <B extiende DataBuffer <?>> | Un contenedor mutable para ver parte de un DataBuffer . |
| Clase de datos | Protobuf enumeración tensorflow.DataClass |
| DataFormatDimMap <T extiende TNumber > | Devuelve el índice de dimensión en el formato de datos de destino dado el de el formato de datos de origen. |
| DataFormatDimMap.Opciones | Atributos opcionales para DataFormatDimMap |
| DataFormatVecPermute <T extiende TNumber > | Permuta el tensor de entrada de `src_format` a `dst_format`. |
| DataFormatVecPermute.Opciones | Atributos opcionales para DataFormatVecPermute |
| DataLayout <S extiende Databuffer <?>, t> | Convierte datos almacenados en un búfer a un tipo dado. |
| DataLayouts | Expone las instancias DataLayout de formatos de datos utilizados con frecuencia en el cálculo de álgebra lineal. |
| Servicio de datos | |
| DataServiceTataSet.OPTIONS | Atributos opcionales para DataServiceDataset |
| Conjunto de datos | Representa una lista potencialmente grande de elementos independientes (muestras), y permite realizar iteración y transformaciones en estos elementos. |
| DataSetCardinality | Devuelve la cardinalidad de `input_dataset`. |
| DataSetCardinality | Devuelve la cardinalidad de `input_dataset`. |
| DataSetFromGraph | Crea un conjunto de datos del `gráfico_def` dado. |
| Conjunto de datos | Representa el estado de una iteración a través de un conjunto de datos TF.Data. |
| Detección de datos | Una opcional representa el resultado de una operación GetNext de conjunto de datos que puede fallar, cuando se ha alcanzado el final del conjunto de datos. |
| Datastograph | Devuelve un GraphDef serializado que representa `input_dataset`. |
| Datasetgraph.options | Atributos opcionales para DatasetToGraph |
| DataSetrosisElement | Emite el elemento único del conjunto de datos dado. |
| DataSettotFrecord | Escribe el conjunto de datos dado en el archivo dado utilizando el formato TFRecord. |
| DataSettotFrecord | Escribe el conjunto de datos dado en el archivo dado utilizando el formato TFRecord. |
| DataStorageVisitor <r> | Visite el almacenamiento de respaldo de las instancias DataBuffer . |
| Tipo de datos | (== suppress_warning documentation-presence ==) LINT.IfChangeProtoBuf enum tensorflow.DataType |
| Dawsn <t extiende tNumber > | |
| DealLocator_pointer_long_pointer | |
| Debugevent | An Event related to the debugging of a TensorFlow program. |
| Debugevent.builder | An Event related to the debugging of a TensorFlow program. |
| Debugevent.whatcase | |
| Debugeventorbuilder | |
| Debugeventprotas | |
| Evice de depuración | A device on which ops and/or tensors are instrumented by the debugger. |
| Debuggeddevice.builder | A device on which ops and/or tensors are instrumented by the debugger. |
| DepuggedDeviceorBuilder | |
| Debuggedgraph | A debugger-instrumented graph. |
| Debuggedgraph.builder | A debugger-instrumented graph. |
| DepuggedGraprapraBuilder | |
| DepuggedSourceFile | ProtoBuf Tipo tensorflow.DebuggedSourceFile |
| DebuggedSourceFile.Builder | ProtoBuf Tipo tensorflow.DebuggedSourceFile |
| DebuggedSourceFileorBuilder | |
| DebuggedSourceFiles | ProtoBuf Tipo tensorflow.DebuggedSourceFiles |
| DebuggedSourceFiles.Builder | ProtoBuf Tipo tensorflow.DebuggedSourceFiles |
| DepuggedSourceFilesorBuilder | |
| DEBUGGRADIENTIONTY <t extiende ttype > | Identidad OP para la depuración de gradiente. |
| DEBUGGRADIENTREFIRETY <t extiende ttype > | Identidad OP para la depuración de gradiente. |
| Deburidentidad <t extiende ttype > | Identidad de depuración v2 op. |
| Debugidentidad.options | Atributos opcionales para DebugIdentity |
| Debugmetata | Metadata about the debugger and the debugged TensorFlow program. |
| Debugmetadata.builder | Metadata about the debugger and the debugged TensorFlow program. |
| DebugMetAdataorBuilder | |
| Depurador | Depurar nan valor contador op. |
| Debugnancount.options | Atributos opcionales para DebugNanCount |
| Debugnumericssummary <u extiende tnumber > | Resumen numérico de depuración v2 op. |
| Debugnumericssummary.options | Atributos opcionales para DebugNumericsSummary |
| Depuiones | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| Debugoptions.builder | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
| DebugptionsorBuilder | |
| Debugprotos | |
| Debugtensorwatch | Option for watching a node in TensorFlow Debugger (tfdbg). |
| Debugtensorwatch.builder | Option for watching a node in TensorFlow Debugger (tfdbg). |
| DebugtensorwatchorBuilder | |
| Decodeandcropjpeg | Decodifique y recorte una imagen codificada por JPEG a un tensor UINT8. |
| Decodeandcropjpeg.options | Atributos opcionales para DecodeAndCropJpeg |
| Decodebase64 | Decodifica cadenas codificadas con base de base Web64. |
| Decodebmp | Decodifique el primer cuadro de una imagen codificada por BMP a un tensor UINT8. |
| Decodebmp.options | Atributos opcionales para DecodeBmp |
| Decodecomprimido | Descompresiones de cuerdas. |
| Decodecompress.options | Atributos opcionales para DecodeCompressed |
| Decodecsv | Convierta los registros de CSV en tensores. |
| Decodecsv.options | Atributos opcionales para DecodeCsv |
| Decodegif | Decodifique la (s) marco (s) de una imagen codificada por GIF a un tensor UINT8. |
| DecodeImage <t extiende tNumber > | Función para decode_bmp, decode_gif, decode_jpeg y decode_png. |
| Decodeimage.options | Atributos opcionales para DecodeImage |
| DecodeJPEG | Decodifique una imagen codificada por JPEG a un tensor UINT8. |
| Decodejpeg.options | Atributos opcionales para DecodeJpeg |
| DecodeJSonexample | Convierta registros de ejemplo codificados por JSON en cadenas de búfer de protocolo binarios. |
| Decodepaddedraw <t extiende tnumber > | Reinterpreten los bytes de una cadena como un vector de números. |
| Decodepaddedraw.options | Atributos opcionales para DecodePaddedRaw |
| Decodepng <t extiende tNumber > | Decodifique una imagen codificada por PNG a un tensor UINT8 o UINT16. |
| Decodepng.options | Atributos opcionales para DecodePng |
| Decodeproto | El OP extrae campos de un mensaje de protocolo serializado en tensores. |
| Decodeproto.options | Atributos opcionales para DecodeProto |
| Decoderaw <t extiende ttype > | Reinterpreten los bytes de una cadena como un vector de números. |
| Decoderaw.options | Atributos opcionales para DecodeRaw |
| Decodewav | Decodifique un archivo WAV PCM de 16 bits a un tensor flotante. |
| Decodewav.options | Atributos opcionales para DecodeWav |
| DeepCopy <t extiende ttype > | Hace una copia de `X`. |
| Delete_func_pointer | |
| Eliminador | Un contenedor para un recurso iterador. |
| DeletememoryCache | |
| Deletemultideviciterator | Un contenedor para un recurso iterador. |
| Dalleandomseedgenerator | |
| Generador de Delesedes | |
| DeleteSessionTensor | Elimine el tensor especificado por su manejo en la sesión. |
| DenseBinCount <u extiende tnumber > | Cuenta el número de ocurrencias de cada valor en una matriz entera. |
| Densebindount.options | Atributos opcionales para DenseBincount |
| DensecountsParseOutput <u extiende tnumber > | Realiza un contado de bin de salida escasa para una entrada tf.tensor. |
| DensecountsParseOutput.OPTIONS | Atributos opcionales para DenseCountSparseOutput |
| DensendArray <T> | |
| Densetocsrsparsematrix | Convierte un tensor denso en una (posiblemente llagada) CSRSPARSEMATRIX. |
| DensetodensesToperation <t extiende ttype > | Aplica la operación establecida a lo largo de la última dimensión de 2 entradas `tensor`. |
| Densetodensesetoperation.options | Atributos opcionales para DenseToDenseSetOperation |
| Densetosparsebatchdataset | Crea un conjunto de datos que llena los elementos de entrada en un SparSetensor. |
| Densetosparsebatchdataset | Crea un conjunto de datos que llena los elementos de entrada en un SparSetensor. |
| DensetosparsesePoperation <t extiende ttype > | Aplica la operación establecida a lo largo de la última dimensión de `tensor` y` sparsetensor`. |
| DensetosparsesePoperation.options | Atributos opcionales para DenseToSparseSetOperation |
| ProfleStoSpace <t extiende ttype > | ProfundirtoSpace para tensores de tipo T. |
| Profundidad. Opciones | Atributos opcionales para DepthToSpace |
| ProfundidadwiseConv2Dnative <t extiende tNumber > | Calcula una convolución en profundidad 2-D dada tensores 4-D `Entrada` y` Filter`. |
| Profundidadwiseconv2dnative.options | Atributos opcionales para DepthwiseConv2dNative |
| ProfundidadwiseConv2DnativeBackPropfilter <t extiende tNumber > | Calcula los gradientes de la convolución en profundidad con respecto al filtro. |
| ProfundidadwiseConv2DnativeBackPropfilter.options | Atributos opcionales para DepthwiseConv2dNativeBackpropFilter |
| ProfundidadwiseConv2DnativeBackPropinput <t extiende tnumber > | Calcula los gradientes de la convolución en profundidad con respecto a la entrada. |
| ProfundidadwiseConv2DnativeBackPropinput.options | Atributos opcionales para DepthwiseConv2dNativeBackpropInput |
| Desquantize <u extiende tnumber > | Desquantiza el tensor de 'entrada' en un tensor flotante o bfloat16. |
| Desastrarse | Toma la entrada UINT32 llena y desempaqueta la entrada a UINT8 para hacer Descantización en el dispositivo. |
| Desquantize.options | Atributos opcionales para Dequantize |
| DeserializeIterator | Convierte el tensor de variante dada en un iterador y lo almacena en el recurso dado. |
| DeserializeManySparse <t extiende ttype > | Deserializar y concatenar `sparsetensors` de un minibatch serializado. |
| Deserializesparse <u extiende ttype > | Deserializar objetos `sparsetensor`. |
| DestroyResourceop | Elimina el recurso especificado por el mango. |
| DestroyResourceop.options | Atributos opcionales para DestroyResourceOp |
| DestroyTemporaryVariable <t extiende ttype > | Destruye la variable temporal y devuelve su valor final. |
| Det <t extiende ttype > | Calcula el determinante de una o más matrices cuadradas. |
| Deviceattributes | ProtoBuf Tipo tensorflow.DeviceAttributes |
| DeviceAttributes.Builder | ProtoBuf Tipo tensorflow.DeviceAttributes |
| DeviceAtTributesRbuilder | |
| Deviceattributesprotas | |
| DispositionFiltersProtas | |
| Dispositivo ININDEX | Devuelva el índice del dispositivo que ejecuta el OP. |
| Devicelocalidad | ProtoBuf Tipo tensorflow.DeviceLocality |
| DeviceLocity.Builder | ProtoBuf Tipo tensorflow.DeviceLocality |
| DeviceLocalityorBuilder | |
| Properties de dispositivos | ProtoBuf tipo tensorflow.DeviceProperties |
| DeviceProperties.Builder | ProtoBuf tipo tensorflow.DeviceProperties |
| DevicePropertiesorBuilder | |
| DispositionPropertiesProtas | |
| Dispositivos | Representa una especificación (posiblemente parcial) para un dispositivo TensorFlow. |
| Devicespec.builder | Una clase de constructor para la clase DeviceSpec . |
| Devicespec.devicetype | |
| Devicestepstats | Tipo de protobuf tensorflow.DeviceStepStats |
| DeviceStepstats.builder | Tipo de protobuf tensorflow.DeviceStepStats |
| DeviceSpstatsorBuilder | |
| Valor | Represents a Python dict keyed by `str`. |
| DictValue.Builder | Represents a Python dict keyed by `str`. |
| DictValueOorBuilder | |
| Digamma <t extiende tNumber > | Calcula psi, la derivada de la lgamma (el registro del valor absoluto de `Gamma (x)`), en cuanto al elemento. |
| Dilation2d <t extiende tNumber > | Calcula la dilatación de la escala de grises de los tensores 4-D `Entrada` y 3-D` Filter`. |
| Dilation2dbackpropfilter <t extiende tNumber > | Calcula el gradiente de la dilatación 2-D morfológica con respecto al filtro. |
| Dilation2dbackpropinput <t extiende tNumber > | Calcula el gradiente de dilatación 2-D morfológica con respecto a la entrada. |
| Dimensión | |
| Espacio dimensional | |
| Dirigido InterlevageAtAset | Un sustituto de `InterleaveedAtAset` en una lista fija de conjuntos de datos` n`. |
| Dirigido InterlevageAtAset | Un sustituto de `InterleaveedAtAset` en una lista fija de conjuntos de datos` n`. |
| Div <t extiende ttype > | Devuelve x / y en cuanto al elemento. |
| Divnonan <t extiende ttype > | Devuelve 0 si el denominador es cero. |
| Dot <t extiende ttype > | Envuelve el operador dotgeneral XLA, documentado en https://www.tensorflow.org/performance/xla/operation_semantics#dotgeneral. |
| Doubledatabuffer | Un DataBuffer de dobles. |
| DoubleDatalAyOut <S extiende Databuffer <? >> | Un DataLayout que convierte los datos almacenados en un búfer en dobles. |
| DoubleDensendArray | |
| DoublendArray | Un NdArray de dobles. |
| DrawboundingBoxes <t extiende tNumber > | Dibuja cajas delimitadoras en un lote de imágenes. |
| DummyiterationCounter | |
| Dummymemorycache | |
| Dummyseedgenerator | |
| DynamicPartition <t extiende ttype > | Partitions `Data` en tensores` num_partitions` utilizando índices de 'Partitions`. |
| Dynamicslice <t extiende ttype > | Envuelve el operador XLA DynamicsLice, documentado en https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice. |
| DynamicStitch <t extiende ttype > | Interleve los valores de los tensores `data` en un solo tensor. |
| DynamicUpdatesLice <t extiende ttype > | Envuelve el operador XLA DynamicUpdatesLice, documentado en https://www.tensorflow.org/performance/xla/operation_semantics#dynamicupdateslice. |
mi
| Eagersession | Un entorno para ejecutar las operaciones de TensorFlow con entusiasmo. |
| Eagersession.devicePlacementPolicy | Controla cómo actuar cuando intentamos ejecutar una operación en un dispositivo determinado, pero algunos tensores de entrada no están en ese dispositivo. |
| Eagersession.options | |
| Edición | Calcula la distancia de edición de Levenshtein (posiblemente normalizada). |
| EditDistance.Options | Atributos opcionales para EditDistance |
| Eig <u extiende ttype > | Calcula la descomposición del propio tiempo de una o más matrices cuadradas. |
| Eig.options | Atributos opcionales para Eig |
| Einsum <t extiende ttype > | Contracción del tensor según la Convención de suma de Einstein. |
| Einsum <t extiende ttype > | Un OP que admite Einsum OP básico con 2 entradas y 1 salida. |
| Elu <t extiende tnumber > | Calcula exponencial lineal: `exp (características) - 1` if <0,` características 'de lo contrario. |
| Elu <t extiende tfloating > | Unidad lineal exponencial. |
| Elugrad <t extiende tnumber > | Calcula los gradientes para la operación lineal exponencial (ELU). |
| Incrustaciones de actividades | Una OP que permite la diferenciación de los incrustaciones de TPU. |
| Vacío <t extiende ttype > | Crea un tensor con la forma dada. |
| Vacío.options | Atributos opcionales para Empty |
| VacíaTensorList | Crea y devuelve una lista de tensor vacía. |
| VacacTensormap | Crea y devuelve un mapa de tensor vacío. |
| EncodeBase64 | Codifique las cadenas en el formato base 64 seguro para la web. |
| EncodeBase64.options | Atributos opcionales para EncodeBase64 |
| EncodeJpeg | JPEG-ENCODE Una imagen. |
| EncodeJpeg.options | Atributos opcionales para EncodeJpeg |
| Codejpegvariable QUIEDA | La imagen de entrada de codificación JPEG con calidad de compresión proporcionada. |
| Encender | PNG-ENCODE Una imagen. |
| Encodepng.options | Atributos opcionales para EncodePng |
| Codeeproto | El OP esenializa los mensajes ProtoBuf proporcionados en los tensores de entrada. |
| Codeproto.options | Atributos opcionales para EncodeProto |
| Codewav | Codifique los datos de audio utilizando el formato de archivo WAV. |
| Punto final | Anotación utilizada para marcar un método de una clase anotada con @Operator que debería generar un punto final en ERROR(Ops/org.tensorflow.op.Ops Ops) o uno de sus grupos. |
| Enqueuetpubbeddingintegerbatch | Un OP que enqueala una lista de tensores de lotes de entrada para tpuembedding. |
| Enqueuetpubbeddingintegerbatch.options | Atributos opcionales para EnqueueTPUEmbeddingIntegerBatch |
| Enqueuetpubbeddingraggedtensorbatch | Facilita la portada del código que usa tf.nn.embedding_lookup (). |
| Enqueuetpubbeddingraggedtensorbatch.options | Atributos opcionales para EnqueueTPUEmbeddingRaggedTensorBatch |
| Enqueuetpuembeddingsparsebatch | Un OP que enqueora los índices de entrada de tpuembring de un sparsetensor. |
| Enqueuetpuembeddingsparsebatch.options | Atributos opcionales para EnqueueTPUEmbeddingSparseBatch |
| Enqueuetpuembeddingsparsetensorbatch | Facilita la portada del código que usa tf.nn.embedding_lookup_sparse (). |
| Enqueuetpuembeddingsparsetensorbatch.options | Atributos opcionales para EnqueueTPUEmbeddingSparseTensorBatch |
| Asegurar <t extiende ttype > | Asegura que la forma del tensor coincida con la forma esperada. |
| Enter <t extiende ttype > | Crea o encuentra un marco infantil, y pone a 'datos' a disposición del marco infantil. |
| Enter.options | Atributos opcionales para Enter |
| Entrada Valor | ProtoBuf Tipo tensorflow.EntryValue |
| EntryValue.Builder | ProtoBuf Tipo tensorflow.EntryValue |
| EntryValue.kindcase | |
| EntryValueOorBuilder | |
| Igual | Devuelve el valor de verdad del elemento (x == y) en cuanto al elemento. |
| Igual.options | Atributos opcionales para Equal |
| Erf <t extiende tNumber > | Calcula la función de error Gauss de `X` en cuanto a elemento. |
| Erfc <t extiende tNumber > | Calcula la función de error complementaria de `X` en cuanto a elemento. |
| erfinv <t extiende tNumber > | |
| Códigos de error | |
| ErrorCodesProtas | |
| Euclideannorm <t extiende ttype > | Calcula la norma euclidiana de elementos a través de las dimensiones de un tensor. |
| Euclideannorm.options | Atributos opcionales para EuclideanNorm |
| Evento | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Event.Builder | Protocol buffer representing an event that happened during the execution of a Brain model. |
| Evento. | |
| EventorBuilder | |
| EventProtas | |
| Ejemplo | ProtoBuf Tipo tensorflow.Example |
| Ejemplo.Builder | ProtoBuf Tipo tensorflow.Example |
| Ejemplo | |
| EJEMPLE DEPARSECONFIGURACIÓN | ProtoBuf Tipo tensorflow.ExampleParserConfiguration |
| EJEMPARSPARSERCONFIGURATION.Builder | ProtoBuf Tipo tensorflow.ExampleParserConfiguration |
| EJEMPARSECONFIGURATIONORBUIREDER | |
| Ejemplo | |
| Ejemplo PROTOS | |
| Ejecutar | OP que carga y ejecuta un programa TPU en un dispositivo TPU. |
| Ejecutordupdatevariables | OP que ejecuta un programa con actualizaciones de variables en el lugar opcionales. |
| Ejecución | Data relating to the eager execution of an op or a Graph. |
| Ejecution.builder | Data relating to the eager execution of an op or a Graph. |
| Compromiso | Define un entorno para crear y ejecutar Operation de TensorFlow s. |
| Ejecutivo de los tipos | |
| EjecutorBuilder | |
| Salir <t extiende ttype > | Sale del marco actual a su marco principal. |
| Exp <t extiende ttype > | Calcula exponencial de x elemento en cuanto a elementos. |
| Expanddims <t extiende ttype > | Inserta una dimensión de 1 en la forma de un tensor. |
| Extint <t extiende tnumber > | |
| Expm1 <t extiende ttype > | Calcula `exp (x) - 1` elemento en cuanto al elemento. |
| Exponencial <t extiende tfloating > | Función de activación exponencial. |
| ExtractGlimpse | Extrae un vistazo del tensor de entrada. |
| ExtractGlimpse.options | Atributos opcionales para ExtractGlimpse |
| ExtractiMagePatches <t extiende ttype > | Extraiga `parches` de` imágenes 'y colóquelos en la dimensión de salida de "profundidad". |
| ExtractJpegShape <t extiende tNumber > | Extraiga la información de forma de una imagen codificada por JPEG. |
| ExtractVolumePatches <t extiende tNumber > | Extraiga `parches` de` input` y póngalos en la dimensión de salida `" profundidad "`. |
F
| Hecho | ENCONTRA UN HECHO SOBRE FACTORIOS. |
| Falsoquantwithminmaxargs | Fake-Quantize el tensor de 'entradas', escriba el tensor de 'salidas' del mismo tipo. |
| Falsoquantwithminmaxargs.options | Atributos opcionales para FakeQuantWithMinMaxArgs |
| Falsoquantwithminmaxargsgradient | Calcule los gradientes para una operación falsa de MinMinmaxargs. |
| Falsoquantwithminmaxargsgradient.options | Atributos opcionales para FakeQuantWithMinMaxArgsGradient |
| Falsoquantwithminmaxvars | Cuantizar falso el tensor de 'insumos' de tipo flotante a través de Global Float Scalars Cuantice falsos el tensor de `entradas` de tipo flotante a través de los escalares flotantes globales` min` y `max` a` salidas` tensor de la misma forma que `entradas '. |
| Falsequantwithminmaxvars.options | Atributos opcionales para FakeQuantWithMinMaxVars |
| Falsoquantwithminmaxvarsgradient | Calcule los gradientes para una operación falsa de MinMinmaxVars. |
| Falsoquantwithminmaxvarsgradient.options | Atributos opcionales para FakeQuantWithMinMaxVarsGradient |
| Falsoquantwithminmaxvarsperchannel | Cantere falso el tensor de 'entradas' de tipo flotante a través de flotadores por canal Cuantiza falso el tensor `entradas` de tipo flotante por canal y una de las formas:` [D] `,` [B, D] `` [B, H, W, D] `a través de flotadores por canal` min` y `max` de forma` [d] `a` salidas` tensor de la misma forma que `entradas '. |
| Falsequantwithminmaxvarsperchannel.options | Atributos opcionales para FakeQuantWithMinMaxVarsPerChannel |
| Falsoquantwithminmaxvarsperchannelgradient | Calcule los gradientes para obtener una operación falsaquantwithminmaxvarsperchannel. |
| Falsequantwithminmaxvarsperchannelgradient.options | Atributos opcionales para FakeQuantWithMinMaxVarsPerChannelGradient |
| FastelementSequence <t, u extiende nDarray <T>> | Una secuencia que recicla la misma instancia NdArray al iterando sus elementos |
| Característica | Containers for non-sequential data. |
| Feing.Builder | Containers for non-sequential data. |
| Feature.kindcase | |
| FeatureConfiguration | ProtoBuf Tipo tensorflow.FeatureConfiguration |
| FeatureConfiguration.Builder | ProtoBuf Tipo tensorflow.FeatureConfiguration |
| FeatureConfiguration.Configcase | |
| FeatureConfigurationorBuilder | |
| Característica | Containers for sequential data. |
| FeeReList.Builder | Containers for sequential data. |
| FeurelistorBuilder | |
| Caracteres | ProtoBuf Tipo tensorflow.FeatureLists |
| Feurelists.builder | ProtoBuf Tipo tensorflow.FeatureLists |
| FeurelistorBuilder | |
| FuncionorBuilder | |
| FeatureProtas | |
| Características | ProtoBuf Tipo tensorflow.Features |
| Características. | ProtoBuf Tipo tensorflow.Features |
| Características | |
| Fft <t extiende ttype > | Transformación rápida de Fourier. |
| Fft2d <t extiende ttype > | 2d transformación rápida de Fourier. |
| Fft3d <t extiende ttype > | 3D Fast Fourier Transform. |
| Fifoceue | Una cola que produce elementos en el primer orden de primera salida. |
| Fifoceue.options | Atributos opcionales para FifoQueue |
| Llenar <u extiende ttype > | Crea un tensor lleno de un valor escalar. |
| FilterBylastComponentDataSet | Crea un conjunto de datos que contiene elementos del primer componente de `input_dataset` que tiene verdadero en el último componente. |
| Huella dactilar | Genera valores de huellas digitales. |
| Fixenfeatureproto | ProtoBuf Tipo tensorflow.FixedLenFeatureProto |
| FixenfeatoProto.builder | ProtoBuf Tipo tensorflow.FixedLenFeatureProto |
| FIXEDLENFeatureProtoorBuilder | |
| Fijo longitudrecorddataSet | |
| Fijo longitudrecordreader | Un lector que genera registros de longitud fija de un archivo. |
| Fijado longitud de longitud | Atributos opcionales para FixedLengthRecordReader |
| Fijounigramcandidatesampler | Genera etiquetas para el muestreo de candidatos con una distribución unigram aprendida. |
| Fixedunigramcandidatesampler.options | Atributos opcionales para FixedUnigramCandidateSampler |
| Float16Layout | Diseño de datos que convierte flotadores de 32 bits de/a 16 bits, en consecuencia a la especificación de punto flotante de media precisión IEEE-754. |
| Floatdatabuffer | Un DataBuffer de flotadores. |
| FloatDatalAyOut <S extiende Databuffer <? >> | Un DataLayout que convierte los datos almacenados en un búfer en flotadores. |
| Floatdensendarray | |
| Lista flotante | ProtoBuf tipo tensorflow.FloatList |
| Floatlist.builder | ProtoBuf tipo tensorflow.FloatList |
| FloatListorBuilder | |
| Floatndarray | Un NdArray de carrozas. |
| Piso <t extiende tnumber > | Devuelve el elemento entero más grande en cuanto a elemento no mayor que x. |
| Floordiv <t extiende ttype > | Devuelve x // y Elemento en cuanto al elemento. |
| Floormod <t extiende tNumber > | Devuelve el resto de la división. |
| FlushSummaryWriter | |
| FractionAlavgPool <t extiende tNumber > | Realiza una agrupación promedio fraccional en la entrada. |
| FraccionAlavgpool.options | Atributos opcionales para FractionalAvgPool |
| FractionAlavgPoolgrad <t extiende tNumber > | Calcula el gradiente de la función FraccionAlavgPool. |
| FractionAlavgpoolgrad.options | Atributos opcionales para FractionalAvgPoolGrad |
| Fractionalmaxpool <t extiende tNumber > | Realiza una agrupación máxima fraccional en la entrada. |
| Fractionalmaxpool.options | Atributos opcionales para FractionalMaxPool |
| FractionalMaxPoolGrad <t extiende tnumber > | Calcula el gradiente de la función FraccionalMaxPool. |
| Fractionalmaxpoolgrad.options | Atributos opcionales para FractionalMaxPoolGrad |
| Fresnelcos <t extiende tnumber > | |
| Fresnelsin <t extiende tnumber > | |
| Ftrl | Optimizador que implementa el algoritmo FTRL. |
| FunctionDef | A function can be instantiated when the runtime can bind every attr with a value. |
| Functiondef.argattrs | Attributes for function arguments. |
| Functiondef.argattrs.builder | Attributes for function arguments. |
| Functiondef.argattrsorBuilder | |
| FunctionDef.Builder | A function can be instantiated when the runtime can bind every attr with a value. |
| Functiondeflibrary | A library is a set of named functions. |
| FunctionDeflibrary.builder | A library is a set of named functions. |
| FunctiondeflibraryorBuilder | |
| FunctiondeforBuilder | |
| FunctionProtas | |
| Functionspec | Represents `FunctionSpec` used in `Function`. |
| FunctionsPec.Builder | Represents `FunctionSpec` used in `Function`. |
| Functionspec.experimentalcompile | Whether the function should be compiled by XLA. |
| FunctionsPecorBuilder | |
| FusedBatchNorm <t extiende tnumber , u extiende tNumber > | Normalización por lotes. |
| Fusedbatchnorm.options | Atributos opcionales para FusedBatchNorm |
| FusedBatchNormGrad <t extiende tnumber , u extiende tnumber > | Gradiente para la normalización por lotes. |
| Fusedbatchnormgrad.options | Atributos opcionales para FusedBatchNormGrad |
| FusedPadConv2d <t extiende tNumber > | Realiza un relleno como preprocesado durante una convolución. |
| FUSSERIZEANDPADCONV2D <t extiende tNumber > | Realiza un cambio de tamaño y acolchado como preproceso durante una convolución. |
| FusedResizeAndPadConv2d.options | Atributos opcionales para FusedResizeAndPadConv2d |
GRAMO
| Reunir <t extiende tNumber > | Acumula mutuamente múltiples tensores de tipo y forma idénticos. |
| Reunir <t extiende ttype > | Recoja rebanadas de `params` eje` eje` de acuerdo con 'índices'. |
| Reunir <t extiende ttype > | Envuelve el operador de recopilación XLA documentado en https://www.tensorflow.org/xla/operation_semantics#gather |
| Recopilar.opciones | Atributos opcionales para Gather |
| Recopilar.opciones | Atributos opcionales para Gather |
| Gathernd <t extiende ttype > | Recoja rebanadas de `params` en un tensor con forma especificada por 'índices'. |
| Gettinv2 <t extiende tnumber > | Acumula mutuamente múltiples tensores de tipo y forma idénticos. |
| Recolectv2.options | Atributos opcionales para GatherV2 |
| GenerateBoundingBoxProposals | Este OP produce una región de intereses a partir de cajas limitantes dadas (bbox_deltas) codificadas WRT Anchors de acuerdo con Eq.2 en ARXIV: 1506.01497 El OP selecciona las cajas de puntuación `pre_nms_topn`, los decodifica con respecto a los anclajes, aplica una supresión no máxima en los cuadros superpuestos con un valor de intersección-over-sindilina (IOU) más alto que el lado más corto es menor que` min_size`. |
| GenerateBoundingBoxProposals.OPTions | Atributos opcionales para GenerateBoundingBoxProposals |
| Generarvocabremapping | Dado un camino a archivos de vocabulario nuevos y antiguos, devuelve un tensor de reasignación de Longitud `num_new_vocab`, donde` reasignar [i] `contiene el número de fila en el vocabulario anterior que corresponde a la fila` i` en el nuevo vocabulario (comenzando en la línea `new_vocab_offset` y hasta` num_new_vocab` entidades), o `------- 1` Si la entrada `I` en el nuevo vocabulario no está en el vocabulario antiguo. |
| Generarvocabremapping.options | Atributos opcionales para GenerateVocabRemapping |
| Getsessionhandle | Almacene el tensor de entrada en el estado de la sesión actual. |
| GetSessionTensor <t extiende ttype > | Obtenga el valor del tensor especificado por su mango. |
| Glorot <t extiende tfloating > | El inicializador Glorot, también llamado inicializador Xavier. |
| Gpuinfo | Protobuf tipo tensorflow.GPUInfo |
| Gpuinfo.builder | Protobuf tipo tensorflow.GPUInfo |
| Gpuinfoorbuilder | |
| Gpuoptions | Protobuf tipo tensorflow.GPUOptions |
| Gpuoptions.builder | Protobuf tipo tensorflow.GPUOptions |
| Gpuoptions.experimental | ProtoBuf Tipo tensorflow.GPUOptions.Experimental |
| GpuOptions.experimental.builder | ProtoBuf Tipo tensorflow.GPUOptions.Experimental |
| GpuOptions.experimental.virtualDevices | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| GpuOptions.experimental.virtualDevices.builder | Configuration for breaking down a visible GPU into multiple "virtual" devices. |
| GpuOptions.experimental.virtualDevicesorBuilder | |
| GpuOptions.experimentalorBuilder | |
| GpuOptionsorBuilder | |
| Gradientdef | GradientDef defines the gradient function of a function defined in a function library. |
| Gradientdef.Builder | GradientDef defines the gradient function of a function defined in a function library. |
| Gradiente DeforBuilder | |
| Gradiente | Optimizador de descenso de gradiente estocástico básico. |
| Degradados | Agrega operaciones para calcular las derivadas parciales de la suma de y s wrt x s, es decir, d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2... Si se establecen los valores de |
| Gradientes. Opciones | Atributos opcionales para Gradients |
| Gráfico | Un gráfico de flujo de datos que representa un cálculo de flujo de tensor. |
| Graph.WhilesUbgraphBuilder | Se utiliza para instanciar una clase abstracta que anula el método BuildSubGraph para construir un subgrafio condicional o de cuerpo durante un bucle de tiempo. |
| Grafdebuginfo | ProtoBuf Tipo tensorflow.GraphDebugInfo |
| Graphdebuginfo.builder | ProtoBuf Tipo tensorflow.GraphDebugInfo |
| Graphdebuginfo.filelineecol | This represents a file/line location in the source code. |
| Graphdebuginfo.filelineecol.builder | This represents a file/line location in the source code. |
| Graphdebuginfo.filelineColorBuilder | |
| Graphdebuginfo.stacktrace | This represents a stack trace which is a ordered list of `FileLineCol`. |
| Graphdebuginfo.stacktrace.builder | This represents a stack trace which is a ordered list of `FileLineCol`. |
| Graphdebuginfo.stacktraceorBuilder | |
| GraphdebuginfoorBuilder | |
| Grafdebuginfoprotos | |
| Graphdef | Represents the graph of operationsProtobuf tipo tensorflow.GraphDef |
| Graphdef.builder | Represents the graph of operationsProtobuf tipo tensorflow.GraphDef |
| GraphdeforBuilder | |
| GraphExecutionTrace | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| GraphExecutionTrace.Builder | Data relating to an execution of a Graph (e.g., an eager execution of a FuncGraph). |
| GraphExecutionTraceorBuilder | |
| GraphopCreation | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| GraphopCreation.Builder | The creation of an op in a TensorFlow Graph (e.g., FuncGraph in TF2). |
| GraphopCreationorBuilder | |
| Grafaperación | Implementación para una Operation agregada como nodo a un Graph . |
| GraphoperationBuilder | Una OperationBuilder para agregar GraphOperation s a un Graph . |
| Gráficos | ProtoBuf Tipo tensorflow.GraphOptions |
| Graphoptions.builder | ProtoBuf Tipo tensorflow.GraphOptions |
| GraphoptionsorBuilder | |
| GraphProtas | |
| GraphTransferconstNodeInfo | ProtoBuf Tipo tensorflow.GraphTransferConstNodeInfo |
| GraphTransferconstnodeinfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferConstNodeInfo |
| GraphTransferconstNodeInfoorBuilder | |
| GraphTransfergraphInputNodeInfo | ProtoBuf Tipo tensorflow.GraphTransferGraphInputNodeInfo |
| GraphTransfergraphInputNodeInfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferGraphInputNodeInfo |
| GraphTransfergraphInputNodeInfoorBuilder | |
| GraphTransfergraphoutPutnodeInfo | ProtoBuf Tipo tensorflow.GraphTransferGraphOutputNodeInfo |
| GraphTransfergraphoutputNodeInfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferGraphOutputNodeInfo |
| GraphTransfergraphoutputNodeInfoorBuilder | |
| Graphtransferinfo | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| GraphTransferinfo.Destination | ProtoBuf enum tensorflow.GraphTransferInfo.Destination |
| GraphTransferinFoorBuilder | |
| Graphtransferinfoproto | |
| GraphTransfernodeInfo | ProtoBuf Tipo tensorflow.GraphTransferNodeInfo |
| GraphTransfernodeinfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferNodeInfo |
| GraphTransferNodeInfoorBuilder | |
| GraphTransferNodeInput | ProtoBuf Tipo tensorflow.GraphTransferNodeInput |
| GraphTransferNodeInput.Builder | ProtoBuf Tipo tensorflow.GraphTransferNodeInput |
| GraphTransferNodeInputInfo | ProtoBuf Tipo tensorflow.GraphTransferNodeInputInfo |
| GraphTransfernodeInputInfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferNodeInputInfo |
| GraphTransfernodeInputInfoorBuilder | |
| GraphTransferNodeInputorBuilder | |
| GraphTransferNodododeOutputInfo | ProtoBuf Tipo tensorflow.GraphTransferNodeOutputInfo |
| GraphTransferNodododeOutputinfo.Builder | ProtoBuf Tipo tensorflow.GraphTransferNodeOutputInfo |
| GraphTransferNododeOutputinFoorBuilder | |
| Mayor que | Devuelve el valor de verdad de (x> y) en cuanto al elemento. |
| Mayor | Devuelve el valor de verdad de (x> = y) en cuanto al elemento. |
| GrublockCell <t extiende tnumber > | Calcula la propagación de la célula GRU para 1 paso de tiempo. |
| GrublockCellgrad <t extiende tNumber > | Calcula la propagación de la célula GRU durante 1 paso de tiempo. |
| GuaranteEconst <t extiende ttype > | Da una garantía al tiempo de ejecución de TF que el tensor de entrada es una constante. |
h
| Hardsigmoid <t extiende tfloating > | Activación sigmoidea dura. |
| Hashtable | Crea una tabla hash no inicializada. |
| Hashtable.options | Atributos opcionales para HashTable |
| <T extiende tfloating > | El inicializador. |
| Ayudantes | Clase de contenedor para métodos centrales que agregan o realizan varias operaciones y devuelven una de ellas. |
| Bisagra | Calcula la pérdida de bisagra entre etiquetas y predicciones. |
| La bisagra <t extiende tnumber > | Una métrica que calcula la métrica de pérdida de bisagra entre etiquetas y predicciones. |
| HISTOGRAMFIXEDWIDTH <u extiende tNumber > | Histograma de retorno de valores. |
| Histogramproto | Serialization format for histogram module in core/lib/histogram/histogram.hProtoBuf tipo tensorflow.HistogramProto |
| HISTOGRAMPROTO.Builder | Serialization format for histogram module in core/lib/histogram/histogram.hProtoBuf tipo tensorflow.HistogramProto |
| HistogramProtoorBuilder | |
| HISTOGRAMSUMMARIO | Emite un tampón de protocolo `summary` con un histograma. |
| HsvTorgb <t extiende tNumber > | Convierta una o más imágenes de HSV a RGB. |
| Huber | Calcula la pérdida de Huber entre etiquetas y predicciones. |
I
| Identidad <t extiende tfloating > | Inicializador que genera la matriz de identidad. |
| Identidad <t extiende ttype > | Devuelva un tensor con la misma forma y contenido que el tensor o valor de entrada. |
| Identidad | Devuelve una lista de tensores con las mismas formas y contenidos que la entrada tensores. |
| Lector de identidad | Un lector que genera el trabajo en cola como clave y valor. |
| IdentityReader.options | Atributos opcionales para IdentityReader |
| IFFT <t extiende ttype > | Transformación inversa de Fourier rápido. |
| Ifft2d <t extiende ttype > | Transformación inversa 2d rápida de Fourier. |
| Ifft3d <t extiende ttype > | Transformación inversa 3D Fast Fourier. |
| Igamma <t extiende tNumber > | Calcule la función gamma incompleta regularizada más baja `p (a, x)`. |
| Igammac <t extiende tNumber > | Calcule la función gamma incompleta superior regularizada `Q (A, X)`. |
| Igammagrada <t extiende tnumber > | Calcula el gradiente de `igamma (a, x)` wrt `a`. |
| Ignorrorsdataset | Crea un conjunto de datos que contiene los elementos de `input_dataset` ignorando los errores. |
| Ignorrorsdataset | Crea un conjunto de datos que contiene los elementos de `input_dataset` ignorando los errores. |
| IgnorErerrorsDataSet.options | Atributos opcionales para IgnoreErrorsDataset |
| IgnorErerrorsDataSet.options | Atributos opcionales para IgnoreErrorsDataset |
| Ilegalrankexception | Excepción lanzada cuando una operación no se puede completar debido al rango de la matriz específica. |
| Imag <u extiende tnumber > | Devuelve la parte imaginaria de un número complejo. |
| ImageProjectIVetransformv2 <t extiende tNumber > | Aplica la transformación dada a cada una de las imágenes. |
| ImageProjectIvetransformv2.options | Atributos opcionales para ImageProjectiveTransformV2 |
| ImageProjectIVetransformv3 <t extiende tNumber > | Aplica la transformación dada a cada una de las imágenes. |
| ImageProjectIvetransformv3.options | Atributos opcionales para ImageProjectiveTransformV3 |
| Imagesummary | Emite un búfer de protocolo `summary` con imágenes. |
| Imagesummary.options | Atributos opcionales para ImageSummary |
| ImmutableConst <t extiende ttype > | Devuelve el tensor inmutable de la región de la memoria. |
| Importación | |
| Índice | Un índice utilizado para cortar una vista de una matriz N-dimensional. |
| IndexedPositionIterator | |
| IndexedPositionerator.coordslongconsumer | |
| Índices | Clase de ayuda para instanciar objetos Index . |
| Infeeddequeue <t extiende ttype > | Un marcador de posición OP por un valor que se alimentará en el cálculo. |
| Confeeddequeuetuple | Obtiene múltiples valores de FEED como una tupla XLA. |
| Infreedenqueue | Un OP que alimenta un solo valor tensor en el cálculo. |
| Infeedenqueue. Opciones | Atributos opcionales para InfeedEnqueue |
| InfeedenqueuePrelinealizedBuffer | Un OP que enqueuza el tampón prelinealizar en la TPU Feed. |
| InfeedenqueuePrelinealizedBuffer.options | Atributos opcionales para InfeedEnqueuePrelinearizedBuffer |
| Infreedenqueuetuple | Alimenta múltiples valores de tensor en el cálculo como una tupla XLA. |
| InfeedenqueUetuple.options | Atributos opcionales para InfeedEnqueueTuple |
| inicio | |
| Inicializador <t extiende ttype > | Una interfaz para inicializadores |
| Inicializable | Inicializador de tabla que toma dos tensores para claves y valores respectivamente. |
| Inicializetable de una dataSet | |
| InicializetableFromTextFile | Inicializa una tabla de un archivo de texto. |
| InicializeTableFromTextFile.options | Atributos opcionales para InitializeTableFromTextFile |
| Inplaceadd <t extiende ttype > | Agrega V a las filas especificadas de x. |
| Inplacesub <t extiende ttype > | Resta `v` en filas especificadas de` x`. |
| InplaceUpdate <t extiende ttype > | Actualizaciones de filas especificadas 'i' con valores 'v'. |
| Int64list | ProtoBuf Tipo tensorflow.Int64List |
| Int64list.builder | ProtoBuf Tipo tensorflow.Int64List |
| Int64ListorBuilder | |
| Intdatabuffer | DataBuffer de INTS. |
| IntdatalAyout <S extiende Databuffer <? >> | Un DataLayout que convierte los datos almacenados en un búfer en INTS. |
| IntdensendArray | |
| Interconexión | ProtoBuf tipo tensorflow.InterconnectLink |
| Interconnectlink.builder | Protobuf type tensorflow.InterconnectLink |
| InterconnectLinkOrBuilder | |
| IntNdArray | An NdArray of integers. |
| InTopK | Says whether the targets are in the top `K` predictions. |
| Inv <T extends TType > | Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes). |
| Inv.Options | Optional attributes for Inv |
| Invert <T extends TNumber > | Invert (flip) each bit of supported types; for example, type `uint8` value 01010101 becomes 10101010. |
| InvertPermutation <T extends TNumber > | Computes the inverse permutation of a tensor. |
| InvGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
| Irfft <U extends TNumber > | Inverse real-valued fast Fourier transform. |
| Irfft2d <U extends TNumber > | Inverse 2D real-valued fast Fourier transform. |
| Irfft3d <U extends TNumber > | Inverse 3D real-valued fast Fourier transform. |
| IsBoostedTreesEnsembleInitialized | Checks whether a tree ensemble has been initialized. |
| IsBoostedTreesQuantileStreamResourceInitialized | Checks whether a quantile stream has been initialized. |
| IsFinite | Returns which elements of x are finite. |
| IsInf | Returns which elements of x are Inf. |
| IsNan | Returns which elements of x are NaN. |
| IsotonicRegression <U extends TNumber > | Solves a batch of isotonic regression problems. |
| IsVariableInitialized | Checks whether a tensor has been initialized. |
| Iterator | |
| IteratorFromStringHandle | |
| IteratorFromStringHandle.Options | Optional attributes for IteratorFromStringHandle |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetDevice | Returns the name of the device on which `resource` has been placed. |
| IteratorGetNext | Gets the next output from the given iterator . |
| IteratorGetNextAsOptional | Gets the next output from the given iterator as an Optional variant. |
| IteratorGetNextSync | Gets the next output from the given iterator. |
| IteratorToStringHandle | Converts the given `resource_handle` representing an iterator to a string. |
j
| JobDef | Defines a single job in a TensorFlow cluster. |
| JobDef.Builder | Defines a single job in a TensorFlow cluster. |
| JobDefOrBuilder | |
| JobDeviceFilters | Defines the device filters for tasks in a job. |
| JobDeviceFilters.Builder | Defines the device filters for tasks in a job. |
| JobDeviceFiltersOrBuilder | |
| Unirse | Joins the strings in the given list of string tensors into one tensor; with the given separator (default is an empty separator). |
| Join.Options | Optional attributes for Join |
k
| KernelDef | Protobuf type tensorflow.KernelDef |
| KernelDef.AttrConstraint | Protobuf type tensorflow.KernelDef.AttrConstraint |
| KernelDef.AttrConstraint.Builder | Protobuf type tensorflow.KernelDef.AttrConstraint |
| KernelDef.AttrConstraintOrBuilder | |
| KernelDef.Builder | Protobuf type tensorflow.KernelDef |
| KernelDefOrBuilder | |
| KernelDefProtos | |
| KernelList | A collection of KernelDefsProtobuf type tensorflow.KernelList |
| KernelList.Builder | A collection of KernelDefsProtobuf type tensorflow.KernelList |
| KernelListOrBuilder | |
| KeyValueSort <T extends TNumber , U extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| KLDivergence | Computes Kullback-Leibler divergence loss between labels and predictions. |
| KLDivergence <T extends TNumber > | A metric that computes the Kullback-Leibler divergence loss metric between labels and predictions. |
| KMC2ChainInitialization | Returns the index of a data point that should be added to the seed set. |
| KmeansPlusPlusInitialization | Selects num_to_sample rows of input using the KMeans++ criterion. |
| KthOrderStatistic | Computes the Kth order statistic of a data set. |
l
| L2Loss <T extends TNumber > | L2 Loss. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LatencyStatsDataset | Records the latency of producing `input_dataset` elements in a StatsAggregator. |
| LeakyRelu <T extends TNumber > | Computes rectified linear: `max(features, features * alpha)`. |
| LeakyRelu.Options | Optional attributes for LeakyRelu |
| LeakyReluGrad <T extends TNumber > | Computes rectified linear gradients for a LeakyRelu operation. |
| LeakyReluGrad.Options | Optional attributes for LeakyReluGrad |
| LearnedUnigramCandidateSampler | Generates labels for candidate sampling with a learned unigram distribution. |
| LearnedUnigramCandidateSampler.Options | Optional attributes for LearnedUnigramCandidateSampler |
| LeCun <T extends TFloating > | LeCun normal initializer. |
| LeftShift <T extends TNumber > | Elementwise computes the bitwise left-shift of `x` and `y`. |
| Menos | Returns the truth value of (x < y) element-wise. |
| LessEqual | Returns the truth value of (x <= y) element-wise. |
| Lgamma <T extends TNumber > | Computes the log of the absolute value of `Gamma(x)` element-wise. |
| Linear <U extends TNumber > | Linear activation function (pass-through). |
| LinSpace <T extends TNumber > | Generates values in an interval. |
| Listener_BytePointer | |
| Listener_String | |
| ListValue | Represents a Python list. |
| ListValue.Builder | Represents a Python list. |
| ListValueOrBuilder | |
| LMDBDataset | Creates a dataset that emits the key-value pairs in one or more LMDB files. |
| LmdbDataset | |
| LmdbReader | A Reader that outputs the records from a LMDB file. |
| LmdbReader.Options | Optional attributes for LmdbReader |
| LoadAndRemapMatrix | Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint at `ckpt_path` and potentially reorders its rows and columns using the specified remappings. |
| LoadAndRemapMatrix.Options | Optional attributes for LoadAndRemapMatrix |
| LoadTPUEmbeddingAdadeltaParameters | Load Adadelta embedding parameters. |
| LoadTPUEmbeddingAdadeltaParameters.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParameters |
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug | Load Adadelta parameters with debug support. |
| LoadTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdadeltaParametersGradAccumDebug |
| LoadTPUEmbeddingAdagradParameters | Load Adagrad embedding parameters. |
| LoadTPUEmbeddingAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingAdagradParameters |
| LoadTPUEmbeddingAdagradParametersGradAccumDebug | Load Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingAdagradParametersGradAccumDebug |
| LoadTPUEmbeddingADAMParameters | Load ADAM embedding parameters. |
| LoadTPUEmbeddingADAMParameters.Options | Optional attributes for LoadTPUEmbeddingADAMParameters |
| LoadTPUEmbeddingADAMParametersGradAccumDebug | Load ADAM embedding parameters with debug support. |
| LoadTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingADAMParametersGradAccumDebug |
| LoadTPUEmbeddingCenteredRMSPropParameters | Load centered RMSProp embedding parameters. |
| LoadTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingCenteredRMSPropParameters |
| LoadTPUEmbeddingFTRLParameters | Load FTRL embedding parameters. |
| LoadTPUEmbeddingFTRLParameters.Options | Optional attributes for LoadTPUEmbeddingFTRLParameters |
| LoadTPUEmbeddingFTRLParametersGradAccumDebug | Load FTRL embedding parameters with debug support. |
| LoadTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingFTRLParametersGradAccumDebug |
| LoadTPUEmbeddingMDLAdagradLightParameters | Load MDL Adagrad Light embedding parameters. |
| LoadTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for LoadTPUEmbeddingMDLAdagradLightParameters |
| LoadTPUEmbeddingMomentumParameters | Load Momentum embedding parameters. |
| LoadTPUEmbeddingMomentumParameters.Options | Optional attributes for LoadTPUEmbeddingMomentumParameters |
| LoadTPUEmbeddingMomentumParametersGradAccumDebug | Load Momentum embedding parameters with debug support. |
| LoadTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingMomentumParametersGradAccumDebug |
| LoadTPUEmbeddingProximalAdagradParameters | Load proximal Adagrad embedding parameters. |
| LoadTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParameters |
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug | Load proximal Adagrad embedding parameters with debug support. |
| LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug |
| LoadTPUEmbeddingProximalYogiParameters | |
| LoadTPUEmbeddingProximalYogiParameters.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParameters |
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| LoadTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingProximalYogiParametersGradAccumDebug |
| LoadTPUEmbeddingRMSPropParameters | Load RMSProp embedding parameters. |
| LoadTPUEmbeddingRMSPropParameters.Options | Optional attributes for LoadTPUEmbeddingRMSPropParameters |
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug | Load RMSProp embedding parameters with debug support. |
| LoadTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingRMSPropParametersGradAccumDebug |
| LoadTPUEmbeddingStochasticGradientDescentParameters | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParameters |
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Load SGD embedding parameters. |
| LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for LoadTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
| LocalLinks | Protobuf type tensorflow.LocalLinks |
| LocalLinks.Builder | Protobuf type tensorflow.LocalLinks |
| LocalLinksOrBuilder | |
| LocalResponseNormalization <T extends TNumber > | Local Response Normalization. |
| LocalResponseNormalization.Options | Optional attributes for LocalResponseNormalization |
| LocalResponseNormalizationGrad <T extends TNumber > | Gradients for Local Response Normalization. |
| LocalResponseNormalizationGrad.Options | Optional attributes for LocalResponseNormalizationGrad |
| Log <T extends TType > | Computes natural logarithm of x element-wise. |
| Log1p <T extends TType > | Computes natural logarithm of (1 + x) element-wise. |
| LogCosh | Computes Computes the logarithm of the hyperbolic cosine of the prediction error. |
| LogCoshError <T extends TNumber > | A metric that computes the logarithm of the hyperbolic cosine of the prediction error metric between labels and predictions. |
| LogicalAnd | Returns the truth value of x AND y element-wise. |
| LogicalNot | Returns the truth value of `NOT x` element-wise. |
| LogicalOr | Returns the truth value of x OR y element-wise. |
| LogMatrixDeterminant <T extends TType > | Computes the sign and the log of the absolute value of the determinant of one or more square matrices. |
| LogMemoryProtos | |
| LogMessage | Protocol buffer used for logging messages to the events file. |
| LogMessage.Builder | Protocol buffer used for logging messages to the events file. |
| LogMessage.Level | Protobuf enum tensorflow.LogMessage.Level |
| LogMessageOrBuilder | |
| LogSoftmax <T extends TNumber > | Computes log softmax activations. |
| LogUniformCandidateSampler | Generates labels for candidate sampling with a log-uniform distribution. |
| LogUniformCandidateSampler.Options | Optional attributes for LogUniformCandidateSampler |
| LongDataBuffer | A DataBuffer of longs. |
| LongDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to longs. |
| LongDenseNdArray | |
| LongNdArray | An NdArray of longs. |
| LookupTableExport <T extends TType , U extends TType > | Outputs all keys and values in the table. |
| LookupTableFind <U extends TType > | Looks up keys in a table, outputs the corresponding values. |
| LookupTableImport | Replaces the contents of the table with the specified keys and values. |
| LookupTableInsert | Updates the table to associates keys with values. |
| LookupTableRemove | Removes keys and its associated values from a table. |
| LookupTableSize | Computes the number of elements in the given table. |
| LoopCond | Forwards the input to the output. |
| Pérdida | |
| Pérdidas | Built-in loss functions. |
| LossesHelper | These are helper methods for Losses and Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| LossMetric <T extends TNumber > | Interface for Metrics that wrap Loss functions. |
| LossTuple <T extends TNumber > | A helper class for loss methods to return labels, target, and sampleWeights |
| Más bajo | Converts all uppercase characters into their respective lowercase replacements. |
| Lower.Options | Optional attributes for Lower |
| LowerBound <U extends TNumber > | Applies lower_bound(sorted_search_values, values) along each row. |
| LSTMBlockCell <T extends TNumber > | Computes the LSTM cell forward propagation for 1 time step. |
| LSTMBlockCell.Options | Optional attributes for LSTMBlockCell |
| LSTMBlockCellGrad <T extends TNumber > | Computes the LSTM cell backward propagation for 1 timestep. |
| Lu <T extends TType , U extends TNumber > | Computes the LU decomposition of one or more square matrices. |
METRO
| MachineConfiguration | Protobuf type tensorflow.MachineConfiguration |
| MachineConfiguration.Builder | Protobuf type tensorflow.MachineConfiguration |
| MachineConfigurationOrBuilder | |
| MakeIterator | Makes a new iterator from the given `dataset` and stores it in `iterator`. |
| MakeUnique | Make all elements in the non-Batch dimension unique, but \"close\" to their initial value. |
| MapClear | Op removes all elements in the underlying container. |
| MapClear.Options | Optional attributes for MapClear |
| MapDataset | |
| MapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| MapIncompleteSize.Options | Optional attributes for MapIncompleteSize |
| MapIterator | |
| MapOptional | |
| MapPeek | Op peeks at the values at the specified key. |
| MapPeek.Options | Optional attributes for MapPeek |
| MapSize | Op returns the number of elements in the underlying container. |
| MapSize.Options | Optional attributes for MapSize |
| MapStage | Stage (key, values) in the underlying container which behaves like a hashtable. |
| MapStage.Options | Optional attributes for MapStage |
| MapUnstage | Op removes and returns the values associated with the key from the underlying container. |
| MapUnstage.Options | Optional attributes for MapUnstage |
| MapUnstageNoKey | Op removes and returns a random (key, value) from the underlying container. |
| MapUnstageNoKey.Options | Optional attributes for MapUnstageNoKey |
| MatchingFiles | Returns the set of files matching one or more glob patterns. |
| MatchingFilesDataset | |
| MatchingFilesDataset | |
| MatMul <T extends TType > | Multiply the matrix "a" by the matrix "b". |
| MatMul.Options | Optional attributes for MatMul |
| MatrixDiag <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagPart <T extends TType > | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3 <T extends TType > | Returns the batched diagonal part of a batched tensor. |
| MatrixDiagPartV3.Options | Optional attributes for MatrixDiagPartV3 |
| MatrixDiagV3 <T extends TType > | Returns a batched diagonal tensor with given batched diagonal values. |
| MatrixDiagV3.Options | Optional attributes for MatrixDiagV3 |
| MatrixLogarithm <T extends TType > | Computes the matrix logarithm of one or more square matrices: \\(log(exp(A)) = A\\) This op is only defined for complex matrices. |
| MatrixSetDiag <T extends TType > | Returns a batched matrix tensor with new batched diagonal values. |
| MatrixSetDiag.Options | Optional attributes for MatrixSetDiag |
| MatrixSolveLs <T extends TType > | Solves one or more linear least-squares problems. |
| MatrixSolveLs.Options | Optional attributes for MatrixSolveLs |
| Max <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
| Max.Options | Optional attributes for Max |
| Maximum <T extends TNumber > | Returns the max of x and y (ie |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxIntraOpParallelismDataset | Creates a dataset that overrides the maximum intra-op parallelism. |
| MaxNorm | Constrains the weights incident to each hidden unit to have a norm less than or equal to a desired value. |
| MaxPool <T extends TType > | Performs max pooling on the input. |
| MaxPool.Options | Optional attributes for MaxPool |
| MaxPool3d <T extends TNumber > | Performs 3D max pooling on the input. |
| MaxPool3d.Options | Optional attributes for MaxPool3d |
| MaxPool3dGrad <U extends TNumber > | Computes gradients of 3D max pooling function. |
| MaxPool3dGrad.Options | Optional attributes for MaxPool3dGrad |
| MaxPool3dGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPool3dGradGrad.Options | Optional attributes for MaxPool3dGradGrad |
| MaxPoolGrad <T extends TNumber > | Computes gradients of the maxpooling function. |
| MaxPoolGrad.Options | Optional attributes for MaxPoolGrad |
| MaxPoolGradGrad <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGrad.Options | Optional attributes for MaxPoolGradGrad |
| MaxPoolGradGradWithArgmax <T extends TNumber > | Computes second-order gradients of the maxpooling function. |
| MaxPoolGradGradWithArgmax.Options | Optional attributes for MaxPoolGradGradWithArgmax |
| MaxPoolGradWithArgmax <T extends TNumber > | Computes gradients of the maxpooling function. |
| MaxPoolGradWithArgmax.Options | Optional attributes for MaxPoolGradWithArgmax |
| MaxPoolWithArgmax <T extends TNumber , U extends TNumber > | Performs max pooling on the input and outputs both max values and indices. |
| MaxPoolWithArgmax.Options | Optional attributes for MaxPoolWithArgmax |
| Mean <T extends TNumber > | A metric that that implements a weighted mean WEIGHTED_MEAN |
| Mean <T extends TType > | Computes the mean of elements across dimensions of a tensor. |
| Mean.Options | Optional attributes for Mean |
| MeanAbsoluteError | Computes the mean of absolute difference between labels and predictions. |
| MeanAbsoluteError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanAbsolutePercentageError | Computes the mean absolute percentage error between labels and predictions. |
| MeanAbsolutePercentageError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanMetricWrapper <T extends TNumber > | A class that bridges a stateless loss function with the Mean metric using a reduction of WEIGHTED_MEAN . |
| MeanSquaredError | Computes the mean of squares of errors between labels and predictions. |
| MeanSquaredError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MeanSquaredLogarithmicError | Computes the mean squared logarithmic errors between labels and predictions. |
| MeanSquaredLogarithmicError <T extends TNumber > | A metric that computes the mean of absolute difference between labels and predictions. |
| MemAllocatorStats | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
| MemAllocatorStats.Builder | Some of the data from AllocatorStatsProtobuf type tensorflow.MemAllocatorStats |
| MemAllocatorStatsOrBuilder | |
| MemChunk | Protobuf type tensorflow.MemChunk |
| MemChunk.Builder | Protobuf type tensorflow.MemChunk |
| MemChunkOrBuilder | |
| MemmappedFileSystemDirectory | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectory.Builder | A directory of regions in a memmapped file. |
| MemmappedFileSystemDirectoryElement | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElement.Builder | A message that describes one region of memmapped file. |
| MemmappedFileSystemDirectoryElementOrBuilder | |
| MemmappedFileSystemDirectoryOrBuilder | |
| MemmappedFileSystemProtos | |
| MemoryDump | Protobuf type tensorflow.MemoryDump |
| MemoryDump.Builder | Protobuf type tensorflow.MemoryDump |
| MemoryDumpOrBuilder | |
| MemoryInfo | Protobuf type tensorflow.MemoryInfo |
| MemoryInfo.Builder | Protobuf type tensorflow.MemoryInfo |
| MemoryInfoOrBuilder | |
| MemoryLogRawAllocation | Protobuf type tensorflow.MemoryLogRawAllocation |
| MemoryLogRawAllocation.Builder | Protobuf type tensorflow.MemoryLogRawAllocation |
| MemoryLogRawAllocationOrBuilder | |
| MemoryLogRawDeallocation | Protobuf type tensorflow.MemoryLogRawDeallocation |
| MemoryLogRawDeallocation.Builder | Protobuf type tensorflow.MemoryLogRawDeallocation |
| MemoryLogRawDeallocationOrBuilder | |
| MemoryLogStep | Protobuf type tensorflow.MemoryLogStep |
| MemoryLogStep.Builder | Protobuf type tensorflow.MemoryLogStep |
| MemoryLogStepOrBuilder | |
| MemoryLogTensorAllocation | Protobuf type tensorflow.MemoryLogTensorAllocation |
| MemoryLogTensorAllocation.Builder | Protobuf type tensorflow.MemoryLogTensorAllocation |
| MemoryLogTensorAllocationOrBuilder | |
| MemoryLogTensorDeallocation | Protobuf type tensorflow.MemoryLogTensorDeallocation |
| MemoryLogTensorDeallocation.Builder | Protobuf type tensorflow.MemoryLogTensorDeallocation |
| MemoryLogTensorDeallocationOrBuilder | |
| MemoryLogTensorOutput | Protobuf type tensorflow.MemoryLogTensorOutput |
| MemoryLogTensorOutput.Builder | Protobuf type tensorflow.MemoryLogTensorOutput |
| MemoryLogTensorOutputOrBuilder | |
| MemoryStats | For memory tracking. |
| MemoryStats.Builder | For memory tracking. |
| MemoryStatsOrBuilder | |
| Merge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
| MergeSummary | Merges summaries. |
| MergeV2Checkpoints | V2 format specific: merges the metadata files of sharded checkpoints. |
| MergeV2Checkpoints.Options | Optional attributes for MergeV2Checkpoints |
| MetaGraphDef | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.Builder | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
| MetaGraphDef.MetaInfoDef | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDef.Builder | Meta information regarding the graph to be exported. |
| MetaGraphDef.MetaInfoDefOrBuilder | |
| MetaGraphDefOrBuilder | |
| MetaGraphProtos | |
| Metric <T extends TNumber > | Base class for Metrics |
| MetricEntry | Protobuf type tensorflow.MetricEntry |
| MetricEntry.Builder | Protobuf type tensorflow.MetricEntry |
| MetricEntryOrBuilder | |
| MetricReduction | Defines the different types of metric reductions |
| Métrica | Helper class with built-in metrics functions. |
| MetricsHelper | These are helper methods for Metrics and will be module private when Java modularity is applied to TensorFlow Java. |
| Mfcc | Transforms a spectrogram into a form that's useful for speech recognition. |
| Mfcc.Options | Optional attributes for Mfcc |
| Min <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
| Min.Options | Optional attributes for Min |
| Minimum <T extends TNumber > | Returns the min of x and y (ie |
| MinMaxNorm | Constrains the weights to have the norm between a lower bound and an upper bound. |
| MirrorPad <T extends TType > | Pads a tensor with mirrored values. |
| MirrorPadGrad <T extends TType > | Gradient op for `MirrorPad` op. |
| MiscDataBufferFactory | Factory of miscellaneous data buffers |
| MlirPassthroughOp | Wraps an arbitrary MLIR computation expressed as a module with a main() function. |
| Mod <T extends TNumber > | Returns element-wise remainder of division. |
| ModelDataset | Identity transformation that models performance. |
| ModelDataset.Options | Optional attributes for ModelDataset |
| Impulso | Stochastic gradient descent plus momentum, either nesterov or traditional. |
| Mul <T extends TType > | Returns x * y element-wise. |
| MulNoNan <T extends TType > | Returns x * y element-wise. |
| MultiDeviceIterator | Creates a MultiDeviceIterator resource. |
| MultiDeviceIteratorFromStringHandle | Generates a MultiDeviceIterator resource from its provided string handle. |
| MultiDeviceIteratorFromStringHandle.Options | Optional attributes for MultiDeviceIteratorFromStringHandle |
| MultiDeviceIteratorGetNextFromShard | Gets next element for the provided shard number. |
| MultiDeviceIteratorInit | Initializes the multi device iterator with the given dataset. |
| MultiDeviceIteratorToStringHandle | Produces a string handle for the given MultiDeviceIterator. |
| Multinomial <U extends TNumber > | Draws samples from a multinomial distribution. |
| Multinomial.Options | Optional attributes for Multinomial |
| MutableDenseHashTable | Creates an empty hash table that uses tensors as the backing store. |
| MutableDenseHashTable.Options | Optional attributes for MutableDenseHashTable |
| MutableHashTable | Creates an empty hash table. |
| MutableHashTable.Options | Optional attributes for MutableHashTable |
| MutableHashTableOfTensors | Creates an empty hash table. |
| MutableHashTableOfTensors.Options | Optional attributes for MutableHashTableOfTensors |
| Mutex | Creates a Mutex resource that can be locked by `MutexLock`. |
| Mutex.Options | Optional attributes for Mutex |
| MutexLock | Locks a mutex resource. |
norte
| Nadam | Nadam Optimizer that implements the NAdam algorithm. |
| NameAttrList | A list of attr names and their values. |
| NameAttrList.Builder | A list of attr names and their values. |
| NameAttrListOrBuilder | |
| NamedDevice | Protobuf type tensorflow.NamedDevice |
| NamedDevice.Builder | Protobuf type tensorflow.NamedDevice |
| NamedDeviceOrBuilder | |
| NamedTensorProto | A pair of tensor name and tensor values. |
| NamedTensorProto.Builder | A pair of tensor name and tensor values. |
| NamedTensorProtoOrBuilder | |
| NamedTensorProtos | |
| NamedTupleValue | Represents Python's namedtuple. |
| NamedTupleValue.Builder | Represents Python's namedtuple. |
| NamedTupleValueOrBuilder | |
| NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
| NcclAllReduce <T extends TNumber > | Outputs a tensor containing the reduction across all input tensors. |
| NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
| NcclBroadcast <T extends TNumber > | Sends `input` to all devices that are connected to the output. |
| NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NcclReduce <T extends TNumber > | Reduces `input` from `num_devices` using `reduction` to a single device. |
| NdArray <T> | A data structure of N-dimensions. |
| NdArrays | Utility class for instantiating NdArray objects. |
| NdArraySequence <T extends NdArray <?>> | A sequence of elements of an N-dimensional array. |
| Ndtri <T extends TNumber > | |
| NearestNeighbors | Selects the k nearest centers for each point. |
| Neg <T extends TType > | Computes numerical negative value element-wise. |
| NegTrain | Training via negative sampling. |
| NextAfter <T extends TNumber > | Returns the next representable value of `x1` in the direction of `x2`, element-wise. |
| NextIteration <T extends TType > | Makes its input available to the next iteration. |
| NioDataBufferFactory | Factory of JDK NIO-based data buffers |
| NodeDef | Protobuf type tensorflow.NodeDef |
| NodeDef.Builder | Protobuf type tensorflow.NodeDef |
| NodeDef.ExperimentalDebugInfo | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
| NodeDef.ExperimentalDebugInfo.Builder | Protobuf type tensorflow.NodeDef.ExperimentalDebugInfo |
| NodeDef.ExperimentalDebugInfoOrBuilder | |
| NodeDefOrBuilder | |
| NodeExecStats | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStats.Builder | Time/size stats recorded for a single execution of a graph node. |
| NodeExecStatsOrBuilder | |
| NodeOutput | Output sizes recorded for a single execution of a graph node. |
| NodeOutput.Builder | Output sizes recorded for a single execution of a graph node. |
| NodeOutputOrBuilder | |
| NodeProto | |
| NonDeterministicInts <U extends TType > | Non-deterministically generates some integers. |
| NoneValue | Represents None. |
| NoneValue.Builder | Represents None. |
| NoneValueOrBuilder | |
| NonMaxSuppression <T extends TNumber > | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high intersection-over-union (IOU) overlap with previously selected boxes. |
| NonMaxSuppression.Options | Optional attributes for NonMaxSuppression |
| NonMaxSuppressionWithOverlaps | Greedily selects a subset of bounding boxes in descending order of score, pruning away boxes that have high overlaps with previously selected boxes. |
| NonNeg | Constrains the weights to be non-negative. |
| NonSerializableDataset | |
| NonSerializableDataset | |
| NoOp | Does nothing. |
| NotBroadcastableException | Exception that indicates that static shapes are not able to broadcast among each other during arithmetic operations. |
| NotEqual | Returns the truth value of (x != y) element-wise. |
| NotEqual.Options | Optional attributes for NotEqual |
| NthElement <T extends TNumber > | Finds values of the `n`-th order statistic for the last dimension. |
| NthElement.Options | Optional attributes for NthElement |
oh
| OneHot <U extends TType > | Returns a one-hot tensor. |
| OneHot.Options | Optional attributes for OneHot |
| Ones <T extends TType > | Initializer that generates tensors initialized to 1. |
| Ones <T extends TType > | An operator creating a constant initialized with ones of the shape given by `dims`. |
| OnesLike <T extends TType > | Returns a tensor of ones with the same shape and type as x. |
| Op. | A logical unit of computation. |
| OpDef | Defines an operation. |
| OpDef.ArgDef | For describing inputs and outputs. |
| OpDef.ArgDef.Builder | For describing inputs and outputs. |
| OpDef.ArgDefOrBuilder | |
| OpDef.AttrDef | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDef.Builder | Description of the graph-construction-time configuration of this Op. |
| OpDef.AttrDefOrBuilder | |
| OpDef.Builder | Defines an operation. |
| OpDefOrBuilder | |
| OpDefProtos | |
| OpDeprecation | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
| OpDeprecation.Builder | Information about version-dependent deprecation of an opProtobuf type tensorflow.OpDeprecation |
| OpDeprecationOrBuilder | |
| Operand <T extends TType > | Interface implemented by operands of a TensorFlow operation. |
| Operandos | Utilities for manipulating operand related types and lists. |
| Operación | Performs computation on Tensors. |
| OperationBuilder | A builder for Operation s. |
| Operador | Annotation used by classes to make TensorFlow operations conveniently accessible via org.tensorflow.op.Ops or one of its groups. |
| OpList | A collection of OpDefsProtobuf type tensorflow.OpList |
| OpList.Builder | A collection of OpDefsProtobuf type tensorflow.OpList |
| OpListOrBuilder | |
| OptimizeDataset | Creates a dataset by applying optimizations to `input_dataset`. |
| OptimizeDataset.Options | Optional attributes for OptimizeDataset |
| OptimizeDatasetV2 | Creates a dataset by applying related optimizations to `input_dataset`. |
| OptimizeDatasetV2.Options | Optional attributes for OptimizeDatasetV2 |
| Optimizador | Base class for gradient optimizers. |
| Optimizer.GradAndVar <T extends TType > | A class that holds a paired gradient and variable. |
| Optimizer.Options | Optional attributes for Optimizer |
| OptimizerOptions | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
| OptimizerOptions.Builder | Options passed to the graph optimizerProtobuf type tensorflow.OptimizerOptions |
| OptimizerOptions.GlobalJitLevel | Control the use of the compiler/jit. |
| OptimizerOptions.Level | Optimization levelProtobuf enum tensorflow.OptimizerOptions.Level |
| OptimizerOptionsOrBuilder | |
| Optimizers | Enumerator used to create a new Optimizer with default parameters. |
| OptionalFromValue | Constructs an Optional variant from a tuple of tensors. |
| OptionalGetValue | Returns the value stored in an Optional variant or raises an error if none exists. |
| OptionalHasValue | Returns true if and only if the given Optional variant has a value. |
| OptionalNone | Creates an Optional variant with no value. |
| OrderedMapClear | Op removes all elements in the underlying container. |
| OrderedMapClear.Options | Optional attributes for OrderedMapClear |
| OrderedMapIncompleteSize | Op returns the number of incomplete elements in the underlying container. |
| OrderedMapIncompleteSize.Options | Optional attributes for OrderedMapIncompleteSize |
| OrderedMapPeek | Op peeks at the values at the specified key. |
| OrderedMapPeek.Options | Optional attributes for OrderedMapPeek |
| OrderedMapSize | Op returns the number of elements in the underlying container. |
| OrderedMapSize.Options | Optional attributes for OrderedMapSize |
| OrderedMapStage | Stage (key, values) in the underlying container which behaves like a ordered associative container. |
| OrderedMapStage.Options | Optional attributes for OrderedMapStage |
| OrderedMapUnstage | Op removes and returns the values associated with the key from the underlying container. |
| OrderedMapUnstage.Options | Optional attributes for OrderedMapUnstage |
| OrderedMapUnstageNoKey | Op removes and returns the (key, value) element with the smallest key from the underlying container. |
| OrderedMapUnstageNoKey.Options | Optional attributes for OrderedMapUnstageNoKey |
| OrdinalSelector | A TPU core selector Op. |
| Orthogonal <T extends TFloating > | Initializer that generates an orthogonal matrix. |
| OutfeedDequeue <T extends TType > | Retrieves a single tensor from the computation outfeed. |
| OutfeedDequeue.Options | Optional attributes for OutfeedDequeue |
| OutfeedDequeueTuple | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueTuple.Options | Optional attributes for OutfeedDequeueTuple |
| OutfeedDequeueTupleV2 | Retrieve multiple values from the computation outfeed. |
| OutfeedDequeueV2 <T extends TType > | Retrieves a single tensor from the computation outfeed. |
| OutfeedEnqueue | Enqueue a Tensor on the computation outfeed. |
| OutfeedEnqueueTuple | Enqueue multiple Tensor values on the computation outfeed. |
| Output <T extends TType > | A symbolic handle to a tensor produced by an Operation . |
PAG
| Pad <T extends TType > | Pads a tensor. |
| Pad <T extends TType > | Wraps the XLA Pad operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#pad . |
| PaddedBatchDataset | Creates a dataset that batches and pads `batch_size` elements from the input. |
| PaddedBatchDataset.Options | Optional attributes for PaddedBatchDataset |
| PaddingFifoQueue | A queue that produces elements in first-in first-out order. |
| PaddingFifoQueue.Options | Optional attributes for PaddingFifoQueue |
| PairValue | Represents a (key, value) pair. |
| PairValue.Builder | Represents a (key, value) pair. |
| PairValueOrBuilder | |
| ParallelConcat <T extends TType > | Concatenates a list of `N` tensors along the first dimension. |
| ParallelDynamicStitch <T extends TType > | Interleave the values from the `data` tensors into a single tensor. |
| ParameterizedTruncatedNormal <U extends TNumber > | Outputs random values from a normal distribution. |
| ParameterizedTruncatedNormal.Options | Optional attributes for ParameterizedTruncatedNormal |
| ParseExample | Transforms a vector of tf.Example protos (as strings) into typed tensors. |
| ParseExampleDataset | Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features. |
| ParseExampleDataset.Options | Optional attributes for ParseExampleDataset |
| ParseSequenceExample | Transforms a vector of tf.io.SequenceExample protos (as strings) into typed tensors. |
| ParseSequenceExample.Options | Optional attributes for ParseSequenceExample |
| ParseSingleExample | Transforms a tf.Example proto (as a string) into typed tensors. |
| ParseSingleSequenceExample | Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors. |
| ParseSingleSequenceExample.Options | Optional attributes for ParseSingleSequenceExample |
| ParseTensor <T extends TType > | Transforms a serialized tensorflow.TensorProto proto into a Tensor. |
| PartitionedInput <T extends TType > | An op that groups a list of partitioned inputs together. |
| PartitionedInput.Options | Optional attributes for PartitionedInput |
| PartitionedOutput <T extends TType > | An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned outputs outside the XLA computation. |
| PartitionedOutput.Options | Optional attributes for PartitionedOutput |
| Placeholder <T extends TType > | A placeholder op for a value that will be fed into the computation. |
| Placeholder.Options | Optional attributes for Placeholder |
| PlaceholderWithDefault <T extends TType > | A placeholder op that passes through `input` when its output is not fed. |
| PlatformInfo | Protobuf type tensorflow.PlatformInfo |
| PlatformInfo.Builder | Protobuf type tensorflow.PlatformInfo |
| PlatformInfoOrBuilder | |
| Poison | Computes the Poisson loss between labels and predictions. |
| Poisson <T extends TNumber > | A metric that computes the poisson loss metric between labels and predictions. |
| Polygamma <T extends TNumber > | Compute the polygamma function \\(\psi^{(n)}(x)\\). |
| PopulationCount | Computes element-wise population count (aka |
| PositionIterator | |
| Pow <T extends TType > | Computes the power of one value to another. |
| PrefetchDataset | Creates a dataset that asynchronously prefetches elements from `input_dataset`. |
| PrefetchDataset.Options | Optional attributes for PrefetchDataset |
| Prelinearize | An op which linearizes one Tensor value to an opaque variant tensor. |
| Prelinearize.Options | Optional attributes for Prelinearize |
| PrelinearizeTuple | An op which linearizes multiple Tensor values to an opaque variant tensor. |
| PrelinearizeTuple.Options | Optional attributes for PrelinearizeTuple |
| PreventGradient <T extends TType > | An identity op that triggers an error if a gradient is requested. |
| PreventGradient.Options | Optional attributes for PreventGradient |
| Imprimir | Prints a string scalar. |
| Print.Options | Optional attributes for Print |
| PriorityQueue | A queue that produces elements sorted by the first component value. |
| PriorityQueue.Options | Optional attributes for PriorityQueue |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| PrivateThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| Prod <T extends TType > | Computes the product of elements across dimensions of a tensor. |
| Prod.Options | Optional attributes for Prod |
| ProfileOptions | Next ID: 11Protobuf type tensorflow.ProfileOptions |
| ProfileOptions.Builder | Next ID: 11Protobuf type tensorflow.ProfileOptions |
| ProfileOptions.DeviceType | Protobuf enum tensorflow.ProfileOptions.DeviceType |
| ProfileOptionsOrBuilder | |
| ProfilerOptionsProtos |
q
| Qr <T extends TType > | Computes the QR decompositions of one or more matrices. |
| Qr.Options | Optional attributes for Qr |
| Quantize <T extends TType > | Quantize the 'input' tensor of type float to 'output' tensor of type 'T'. |
| Quantize.Options | Optional attributes for Quantize |
| QuantizeAndDequantize <T extends TNumber > | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantize.Options | Optional attributes for QuantizeAndDequantize |
| QuantizeAndDequantizeV3 <T extends TNumber > | Quantizes then dequantizes a tensor. |
| QuantizeAndDequantizeV3.Options | Optional attributes for QuantizeAndDequantizeV3 |
| QuantizeAndDequantizeV4 <T extends TNumber > | Returns the gradient of `quantization.QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4.Options | Optional attributes for QuantizeAndDequantizeV4 |
| QuantizeAndDequantizeV4Grad <T extends TNumber > | Returns the gradient of `QuantizeAndDequantizeV4`. |
| QuantizeAndDequantizeV4Grad.Options | Optional attributes for QuantizeAndDequantizeV4Grad |
| QuantizedAdd <V extends TType > | Returns x + y element-wise, working on quantized buffers. |
| QuantizedAvgPool <T extends TType > | Produces the average pool of the input tensor for quantized types. |
| QuantizedBatchNormWithGlobalNormalization <U extends TType > | Quantized Batch normalization. |
| QuantizedBiasAdd <V extends TType > | Adds Tensor 'bias' to Tensor 'input' for Quantized types. |
| QuantizedConcat <T extends TType > | Concatenates quantized tensors along one dimension. |
| QuantizedConv2d <V extends TType > | Computes a 2D convolution given quantized 4D input and filter tensors. |
| QuantizedConv2d.Options | Optional attributes for QuantizedConv2d |
| QuantizedConv2DAndRelu <V extends TType > | |
| QuantizedConv2DAndRelu.Options | Optional attributes for QuantizedConv2DAndRelu |
| QuantizedConv2DAndReluAndRequantize <V extends TType > | |
| QuantizedConv2DAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DAndReluAndRequantize |
| QuantizedConv2DAndRequantize <V extends TType > | |
| QuantizedConv2DAndRequantize.Options | Optional attributes for QuantizedConv2DAndRequantize |
| QuantizedConv2DPerChannel <V extends TType > | Computes QuantizedConv2D per channel. |
| QuantizedConv2DPerChannel.Options | Optional attributes for QuantizedConv2DPerChannel |
| QuantizedConv2DWithBias <V extends TType > | |
| QuantizedConv2DWithBias.Options | Optional attributes for QuantizedConv2DWithBias |
| QuantizedConv2DWithBiasAndRelu <V extends TType > | |
| QuantizedConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasAndRelu |
| QuantizedConv2DWithBiasAndReluAndRequantize <W extends TType > | |
| QuantizedConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndReluAndRequantize |
| QuantizedConv2DWithBiasAndRequantize <W extends TType > | |
| QuantizedConv2DWithBiasAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasAndRequantize |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize <X extends TType > | |
| QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSignedSumAndReluAndRequantize |
| QuantizedConv2DWithBiasSumAndRelu <V extends TType > | |
| QuantizedConv2DWithBiasSumAndRelu.Options | Optional attributes for QuantizedConv2DWithBiasSumAndRelu |
| QuantizedConv2DWithBiasSumAndReluAndRequantize <X extends TType > | |
| QuantizedConv2DWithBiasSumAndReluAndRequantize.Options | Optional attributes for QuantizedConv2DWithBiasSumAndReluAndRequantize |
| QuantizedDepthwiseConv2D <V extends TType > | Computes quantized depthwise Conv2D. |
| QuantizedDepthwiseConv2D.Options | Optional attributes for QuantizedDepthwiseConv2D |
| QuantizedDepthwiseConv2DWithBias <V extends TType > | Computes quantized depthwise Conv2D with Bias. |
| QuantizedDepthwiseConv2DWithBias.Options | Optional attributes for QuantizedDepthwiseConv2DWithBias |
| QuantizedDepthwiseConv2DWithBiasAndRelu <V extends TType > | Computes quantized depthwise Conv2D with Bias and Relu. |
| QuantizedDepthwiseConv2DWithBiasAndRelu.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndRelu |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize <W extends TType > | Computes quantized depthwise Conv2D with Bias, Relu and Requantize. |
| QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize |
| QuantizedInstanceNorm <T extends TType > | Quantized Instance normalization. |
| QuantizedInstanceNorm.Options | Optional attributes for QuantizedInstanceNorm |
| QuantizedMatMul <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b`. |
| QuantizedMatMul.Options | Optional attributes for QuantizedMatMul |
| QuantizedMatMulWithBias <W extends TType > | Performs a quantized matrix multiplication of `a` by the matrix `b` with bias add. |
| QuantizedMatMulWithBias.Options | Optional attributes for QuantizedMatMulWithBias |
| QuantizedMatMulWithBiasAndDequantize <W extends TNumber > | |
| QuantizedMatMulWithBiasAndDequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndDequantize |
| QuantizedMatMulWithBiasAndRelu <V extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu fusion. |
| QuantizedMatMulWithBiasAndRelu.Options | Optional attributes for QuantizedMatMulWithBiasAndRelu |
| QuantizedMatMulWithBiasAndReluAndRequantize <W extends TType > | Perform a quantized matrix multiplication of `a` by the matrix `b` with bias add and relu and requantize fusion. |
| QuantizedMatMulWithBiasAndReluAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndReluAndRequantize |
| QuantizedMatMulWithBiasAndRequantize <W extends TType > | |
| QuantizedMatMulWithBiasAndRequantize.Options | Optional attributes for QuantizedMatMulWithBiasAndRequantize |
| QuantizedMaxPool <T extends TType > | Produces the max pool of the input tensor for quantized types. |
| QuantizedMul <V extends TType > | Returns x * y element-wise, working on quantized buffers. |
| QuantizeDownAndShrinkRange <U extends TType > | Convert the quantized 'input' tensor into a lower-precision 'output', using the actual distribution of the values to maximize the usage of the lower bit depth and adjusting the output min and max ranges accordingly. |
| QuantizedRelu <U extends TType > | Computes Quantized Rectified Linear: `max(features, 0)` |
| QuantizedRelu6 <U extends TType > | Computes Quantized Rectified Linear 6: `min(max(features, 0), 6)` |
| QuantizedReluX <U extends TType > | Computes Quantized Rectified Linear X: `min(max(features, 0), max_value)` |
| QuantizedReshape <T extends TType > | Reshapes a quantized tensor as per the Reshape op. |
| QuantizedResizeBilinear <T extends TType > | Resize quantized `images` to `size` using quantized bilinear interpolation. |
| QuantizedResizeBilinear.Options | Optional attributes for QuantizedResizeBilinear |
| QueueClose | Closes the given queue. |
| QueueClose.Options | Optional attributes for QueueClose |
| QueueDequeue | Dequeues a tuple of one or more tensors from the given queue. |
| QueueDequeue.Options | Optional attributes for QueueDequeue |
| QueueDequeueMany | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueMany.Options | Optional attributes for QueueDequeueMany |
| QueueDequeueUpTo | Dequeues `n` tuples of one or more tensors from the given queue. |
| QueueDequeueUpTo.Options | Optional attributes for QueueDequeueUpTo |
| QueueEnqueue | Enqueues a tuple of one or more tensors in the given queue. |
| QueueEnqueue.Options | Optional attributes for QueueEnqueue |
| QueueEnqueueMany | Enqueues zero or more tuples of one or more tensors in the given queue. |
| QueueEnqueueMany.Options | Optional attributes for QueueEnqueueMany |
| QueueIsClosed | Returns true if queue is closed. |
| QueueRunnerDef | Protocol buffer representing a QueueRunner. |
| QueueRunnerDef.Builder | Protocol buffer representing a QueueRunner. |
| QueueRunnerDefOrBuilder | |
| QueueRunnerProtos | |
| QueueSize | Computes the number of elements in the given queue. |
R
| RaggedBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
| RaggedBincount.Options | Optional attributes for RaggedBincount |
| RaggedCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a ragged tensor input. |
| RaggedCountSparseOutput.Options | Optional attributes for RaggedCountSparseOutput |
| RaggedCross <T extends TType , U extends TNumber > | Generates a feature cross from a list of tensors, and returns it as a RaggedTensor. |
| RaggedGather <T extends TNumber , U extends TType > | Gather ragged slices from `params` axis `0` according to `indices`. |
| RaggedRange <U extends TNumber , T extends TNumber > | Returns a `RaggedTensor` containing the specified sequences of numbers. |
| RaggedTensorFromVariant <U extends TNumber , T extends TType > | Decodes a `variant` Tensor into a `RaggedTensor`. |
| RaggedTensorToSparse <U extends TType > | Converts a `RaggedTensor` into a `SparseTensor` with the same values. |
| RaggedTensorToTensor <U extends TType > | Create a dense tensor from a ragged tensor, possibly altering its shape. |
| RaggedTensorToVariant | Encodes a `RaggedTensor` into a `variant` Tensor. |
| RaggedTensorToVariantGradient <U extends TType > | Helper used to compute the gradient for `RaggedTensorToVariant`. |
| RandomCrop <T extends TNumber > | Randomly crop `image`. |
| RandomCrop.Options | Optional attributes for RandomCrop |
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomDataset | Creates a Dataset that returns pseudorandom numbers. |
| RandomGamma <U extends TNumber > | Outputs random values from the Gamma distribution(s) described by alpha. |
| RandomGamma.Options | Optional attributes for RandomGamma |
| RandomGammaGrad <T extends TNumber > | Computes the derivative of a Gamma random sample wrt |
| RandomNormal <T extends TFloating > | Initializer that generates tensors with a normal distribution. |
| RandomPoisson <V extends TNumber > | Outputs random values from the Poisson distribution(s) described by rate. |
| RandomPoisson.Options | Optional attributes for RandomPoisson |
| RandomShuffle <T extends TType > | Randomly shuffles a tensor along its first dimension. |
| RandomShuffle.Options | Optional attributes for RandomShuffle |
| RandomShuffleQueue | A queue that randomizes the order of elements. |
| RandomShuffleQueue.Options | Optional attributes for RandomShuffleQueue |
| RandomStandardNormal <U extends TNumber > | Outputs random values from a normal distribution. |
| RandomStandardNormal.Options | Optional attributes for RandomStandardNormal |
| RandomUniform <T extends TNumber > | Initializer that generates tensors with a uniform distribution. |
| RandomUniform <U extends TNumber > | Outputs random values from a uniform distribution. |
| RandomUniform.Options | Optional attributes for RandomUniform |
| RandomUniformInt <U extends TNumber > | Outputs random integers from a uniform distribution. |
| RandomUniformInt.Options | Optional attributes for RandomUniformInt |
| Range <T extends TNumber > | Creates a sequence of numbers. |
| RangeDataset | Creates a dataset with a range of values. |
| Rango | Returns the rank of a tensor. |
| RawDataBufferFactory | Factory of raw data buffers |
| RawOp | A base class for Op implementations that are backed by a single Operation . |
| RawTensor | A tensor which memory has not been mapped to a data space directly accessible from the JVM. |
| ReaderBaseProtos | |
| ReaderBaseState | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseState.Builder | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
| ReaderBaseStateOrBuilder | |
| ReaderNumRecordsProduced | Returns the number of records this Reader has produced. |
| ReaderNumWorkUnitsCompleted | Returns the number of work units this Reader has finished processing. |
| ReaderRead | Returns the next record (key, value pair) produced by a Reader. |
| ReaderReadUpTo | Returns up to `num_records` (key, value) pairs produced by a Reader. |
| ReaderReset | Restore a Reader to its initial clean state. |
| ReaderRestoreState | Restore a reader to a previously saved state. |
| ReaderSerializeState | Produce a string tensor that encodes the state of a Reader. |
| Leer archivo | Reads and outputs the entire contents of the input filename. |
| ReadVariableOp <T extends TType > | Reads the value of a variable. |
| Real <U extends TNumber > | Returns the real part of a complex number. |
| RealDiv <T extends TType > | Returns x / y element-wise for real types. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset | Creates a dataset that changes the batch size. |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDataset.Options | Optional attributes for RebatchDataset |
| RebatchDatasetV2 | Creates a dataset that changes the batch size. |
| Reciprocal <T extends TType > | Computes the reciprocal of x element-wise. |
| ReciprocalGrad <T extends TType > | Computes the gradient for the inverse of `x` wrt its input. |
| RecordInput | Emits randomized records. |
| RecordInput.Options | Optional attributes for RecordInput |
| Recv <T extends TType > | Receives the named tensor from send_device on recv_device. |
| Recv <T extends TType > | Receives the named tensor from another XLA computation. |
| Recv.Options | Optional attributes for Recv |
| RecvTPUEmbeddingActivations | An op that receives embedding activations on the TPU. |
| Reduce <T extends TNumber > | Encapsulates metrics that perform a reduce operation on the metric values. |
| Reduce <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
| Reduce.Options | Optional attributes for Reduce |
| ReduceAll | Computes the "logical and" of elements across dimensions of a tensor. |
| ReduceAll.Options | Optional attributes for ReduceAll |
| ReduceAny | Computes the "logical or" of elements across dimensions of a tensor. |
| ReduceAny.Options | Optional attributes for ReduceAny |
| ReduceJoin | Joins a string Tensor across the given dimensions. |
| ReduceJoin.Options | Optional attributes for ReduceJoin |
| ReduceMax <T extends TType > | Computes the maximum of elements across dimensions of a tensor. |
| ReduceMax.Options | Optional attributes for ReduceMax |
| ReduceMin <T extends TType > | Computes the minimum of elements across dimensions of a tensor. |
| ReduceMin.Options | Optional attributes for ReduceMin |
| ReduceProd <T extends TType > | Computes the product of elements across dimensions of a tensor. |
| ReduceProd.Options | Optional attributes for ReduceProd |
| ReduceSum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
| ReduceSum.Options | Optional attributes for ReduceSum |
| ReduceV2 <T extends TNumber > | Mutually reduces multiple tensors of identical type and shape. |
| ReduceV2.Options | Optional attributes for ReduceV2 |
| Reducción | Type of Loss Reduction |
| RefEnter <T extends TType > | Creates or finds a child frame, and makes `data` available to the child frame. |
| RefEnter.Options | Optional attributes for RefEnter |
| RefExit <T extends TType > | Exits the current frame to its parent frame. |
| RefIdentity <T extends TType > | Return the same ref tensor as the input ref tensor. |
| RefMerge <T extends TType > | Forwards the value of an available tensor from `inputs` to `output`. |
| RefNextIteration <T extends TType > | Makes its input available to the next iteration. |
| RefSelect <T extends TType > | Forwards the `index`th element of `inputs` to `output`. |
| RefSwitch <T extends TType > | Forwards the ref tensor `data` to the output port determined by `pred`. |
| RegexFullMatch | Check if the input matches the regex pattern. |
| RegexReplace | Replaces matches of the `pattern` regular expression in `input` with the replacement string provided in `rewrite`. |
| RegexReplace.Options | Optional attributes for RegexReplace |
| RegisterDataset | Registers a dataset with the tf.data service. |
| RelativeDimensionalSpace | |
| Relu <T extends TType > | Computes rectified linear: `max(features, 0)`. |
| ReLU <T extends TNumber > | Rectified Linear Unit(ReLU) activation. |
| Relu6 <T extends TNumber > | Computes rectified linear 6: `min(max(features, 0), 6)`. |
| Relu6Grad <T extends TNumber > | Computes rectified linear 6 gradients for a Relu6 operation. |
| ReluGrad <T extends TNumber > | Computes rectified linear gradients for a Relu operation. |
| RemoteFusedGraphExecute | Execute a sub graph on a remote processor. |
| RemoteFusedGraphExecuteInfo | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProto.Builder | Protobuf type tensorflow.RemoteFusedGraphExecuteInfo.TensorShapeTypeProto |
| RemoteFusedGraphExecuteInfo.TensorShapeTypeProtoOrBuilder | |
| RemoteFusedGraphExecuteInfoOrBuilder | |
| RemoteFusedGraphExecuteInfoProto | |
| RemoteProfilerSessionManagerOptions | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptions.Builder | Options for remote profiler session manager. |
| RemoteProfilerSessionManagerOptionsOrBuilder | |
| RemoteTensorHandle | Protobuf type tensorflow.eager.RemoteTensorHandle |
| RemoteTensorHandle.Builder | Protobuf type tensorflow.eager.RemoteTensorHandle |
| RemoteTensorHandleOrBuilder | |
| RemoteTensorHandleProtos | |
| RepeatDataset | Creates a dataset that emits the outputs of `input_dataset` `count` times. |
| ReplicaId | Replica ID. |
| ReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
| ReplicatedInput.Options | Optional attributes for ReplicatedInput |
| ReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
| ReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| ReplicateMetadata.Options | Optional attributes for ReplicateMetadata |
| RequantizationRange | Computes a range that covers the actual values present in a quantized tensor. |
| RequantizationRangePerChannel | Computes requantization range per channel. |
| Requantize <U extends TType > | Converts the quantized `input` tensor into a lower-precision `output`. |
| RequantizePerChannel <U extends TType > | Requantizes input with min and max values known per channel. |
| RequestedExitCode | Protobuf type tensorflow.RequestedExitCode |
| RequestedExitCode.Builder | Protobuf type tensorflow.RequestedExitCode |
| RequestedExitCodeOrBuilder | |
| Reshape <T extends TType > | Reshapes a tensor. |
| ResizeArea | Resize `images` to `size` using area interpolation. |
| ResizeArea.Options | Optional attributes for ResizeArea |
| ResizeBicubic | Resize `images` to `size` using bicubic interpolation. |
| ResizeBicubic.Options | Optional attributes for ResizeBicubic |
| ResizeBicubicGrad <T extends TNumber > | Computes the gradient of bicubic interpolation. |
| ResizeBicubicGrad.Options | Optional attributes for ResizeBicubicGrad |
| ResizeBilinear | Resize `images` to `size` using bilinear interpolation. |
| ResizeBilinear.Options | Optional attributes for ResizeBilinear |
| ResizeBilinearGrad <T extends TNumber > | Computes the gradient of bilinear interpolation. |
| ResizeBilinearGrad.Options | Optional attributes for ResizeBilinearGrad |
| ResizeNearestNeighbor <T extends TNumber > | Resize `images` to `size` using nearest neighbor interpolation. |
| ResizeNearestNeighbor.Options | Optional attributes for ResizeNearestNeighbor |
| ResizeNearestNeighborGrad <T extends TNumber > | Computes the gradient of nearest neighbor interpolation. |
| ResizeNearestNeighborGrad.Options | Optional attributes for ResizeNearestNeighborGrad |
| ResourceAccumulatorApplyGradient | Applies a gradient to a given accumulator. |
| ResourceAccumulatorNumAccumulated | Returns the number of gradients aggregated in the given accumulators. |
| ResourceAccumulatorSetGlobalStep | Updates the accumulator with a new value for global_step. |
| ResourceAccumulatorTakeGradient <T extends TType > | Extracts the average gradient in the given ConditionalAccumulator. |
| ResourceApplyAdadelta | Update '*var' according to the adadelta scheme. |
| ResourceApplyAdadelta.Options | Optional attributes for ResourceApplyAdadelta |
| ResourceApplyAdagrad | Update '*var' according to the adagrad scheme. |
| ResourceApplyAdagrad.Options | Optional attributes for ResourceApplyAdagrad |
| ResourceApplyAdagradDa | Update '*var' according to the proximal adagrad scheme. |
| ResourceApplyAdagradDa.Options | Optional attributes for ResourceApplyAdagradDa |
| ResourceApplyAdam | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdam.Options | Optional attributes for ResourceApplyAdam |
| ResourceApplyAdaMax | Update '*var' according to the AdaMax algorithm. |
| ResourceApplyAdaMax.Options | Optional attributes for ResourceApplyAdaMax |
| ResourceApplyAdamWithAmsgrad | Update '*var' according to the Adam algorithm. |
| ResourceApplyAdamWithAmsgrad.Options | Optional attributes for ResourceApplyAdamWithAmsgrad |
| ResourceApplyAddSign | Update '*var' according to the AddSign update. |
| ResourceApplyAddSign.Options | Optional attributes for ResourceApplyAddSign |
| ResourceApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceApplyCenteredRmsProp.Options | Optional attributes for ResourceApplyCenteredRmsProp |
| ResourceApplyFtrl | Update '*var' according to the Ftrl-proximal scheme. |
| ResourceApplyFtrl.Options | Optional attributes for ResourceApplyFtrl |
| ResourceApplyGradientDescent | Update '*var' by subtracting 'alpha' * 'delta' from it. |
| ResourceApplyGradientDescent.Options | Optional attributes for ResourceApplyGradientDescent |
| ResourceApplyKerasMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyKerasMomentum.Options | Optional attributes for ResourceApplyKerasMomentum |
| ResourceApplyMomentum | Update '*var' according to the momentum scheme. |
| ResourceApplyMomentum.Options | Optional attributes for ResourceApplyMomentum |
| ResourceApplyPowerSign | Update '*var' according to the AddSign update. |
| ResourceApplyPowerSign.Options | Optional attributes for ResourceApplyPowerSign |
| ResourceApplyProximalAdagrad | Update '*var' and '*accum' according to FOBOS with Adagrad learning rate. |
| ResourceApplyProximalAdagrad.Options | Optional attributes for ResourceApplyProximalAdagrad |
| ResourceApplyProximalGradientDescent | Update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceApplyProximalGradientDescent.Options | Optional attributes for ResourceApplyProximalGradientDescent |
| ResourceApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceApplyRmsProp.Options | Optional attributes for ResourceApplyRmsProp |
| ResourceConditionalAccumulator | A conditional accumulator for aggregating gradients. |
| ResourceConditionalAccumulator.Options | Optional attributes for ResourceConditionalAccumulator |
| ResourceCountUpTo <T extends TNumber > | Increments variable pointed to by 'resource' until it reaches 'limit'. |
| ResourceDtypeAndShape | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
| ResourceDtypeAndShape.Builder | Protobuf type tensorflow.eager.ResourceDtypeAndShape |
| ResourceDtypeAndShapeOrBuilder | |
| ResourceGather <U extends TType > | Gather slices from the variable pointed to by `resource` according to `indices`. |
| ResourceGather.Options | Optional attributes for ResourceGather |
| ResourceGatherNd <U extends TType > | |
| ResourceHandle | |
| ResourceHandleProto | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.Builder | Protocol buffer representing a handle to a tensorflow resource. |
| ResourceHandleProto.DtypeAndShape | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShape.Builder | Protocol buffer representing a pair of (data type, tensor shape). |
| ResourceHandleProto.DtypeAndShapeOrBuilder | |
| ResourceHandleProtoOrBuilder | |
| ResourceScatterAdd | Adds sparse updates to the variable referenced by `resource`. |
| ResourceScatterDiv | Divides sparse updates into the variable referenced by `resource`. |
| ResourceScatterMax | Reduces sparse updates into the variable referenced by `resource` using the `max` operation. |
| ResourceScatterMin | Reduces sparse updates into the variable referenced by `resource` using the `min` operation. |
| ResourceScatterMul | Multiplies sparse updates into the variable referenced by `resource`. |
| ResourceScatterNdAdd | Applies sparse addition to individual values or slices in a Variable. |
| ResourceScatterNdAdd.Options | Optional attributes for ResourceScatterNdAdd |
| ResourceScatterNdMax | |
| ResourceScatterNdMax.Options | Optional attributes for ResourceScatterNdMax |
| ResourceScatterNdMin | |
| ResourceScatterNdMin.Options | Optional attributes for ResourceScatterNdMin |
| ResourceScatterNdSub | Applies sparse subtraction to individual values or slices in a Variable. |
| ResourceScatterNdSub.Options | Optional attributes for ResourceScatterNdSub |
| ResourceScatterNdUpdate | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ResourceScatterNdUpdate.Options | Optional attributes for ResourceScatterNdUpdate |
| ResourceScatterSub | Subtracts sparse updates from the variable referenced by `resource`. |
| ResourceScatterUpdate | Assigns sparse updates to the variable referenced by `resource`. |
| ResourceSparseApplyAdadelta | var: Should be from a Variable(). |
| ResourceSparseApplyAdadelta.Options | Optional attributes for ResourceSparseApplyAdadelta |
| ResourceSparseApplyAdagrad | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagrad.Options | Optional attributes for ResourceSparseApplyAdagrad |
| ResourceSparseApplyAdagradDa | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| ResourceSparseApplyAdagradDa.Options | Optional attributes for ResourceSparseApplyAdagradDa |
| ResourceSparseApplyAdagradV2 | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| ResourceSparseApplyAdagradV2.Options | Optional attributes for ResourceSparseApplyAdagradV2 |
| ResourceSparseApplyCenteredRmsProp | Update '*var' according to the centered RMSProp algorithm. |
| ResourceSparseApplyCenteredRmsProp.Options | Optional attributes for ResourceSparseApplyCenteredRmsProp |
| ResourceSparseApplyFtrl | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| ResourceSparseApplyFtrl.Options | Optional attributes for ResourceSparseApplyFtrl |
| ResourceSparseApplyKerasMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyKerasMomentum.Options | Optional attributes for ResourceSparseApplyKerasMomentum |
| ResourceSparseApplyMomentum | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| ResourceSparseApplyMomentum.Options | Optional attributes for ResourceSparseApplyMomentum |
| ResourceSparseApplyProximalAdagrad | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| ResourceSparseApplyProximalAdagrad.Options | Optional attributes for ResourceSparseApplyProximalAdagrad |
| ResourceSparseApplyProximalGradientDescent | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| ResourceSparseApplyProximalGradientDescent.Options | Optional attributes for ResourceSparseApplyProximalGradientDescent |
| ResourceSparseApplyRmsProp | Update '*var' according to the RMSProp algorithm. |
| ResourceSparseApplyRmsProp.Options | Optional attributes for ResourceSparseApplyRmsProp |
| ResourceStridedSliceAssign | Assign `value` to the sliced l-value reference of `ref`. |
| ResourceStridedSliceAssign.Options | Optional attributes for ResourceStridedSliceAssign |
| Restaurar | Restores tensors from a V2 checkpoint. |
| RestoreSlice <T extends TType > | Restores a tensor from checkpoint files. |
| RestoreSlice.Options | Optional attributes for RestoreSlice |
| RetrieveTPUEmbeddingAdadeltaParameters | Retrieve Adadelta embedding parameters. |
| RetrieveTPUEmbeddingAdadeltaParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParameters |
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug | Retrieve Adadelta embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug |
| RetrieveTPUEmbeddingAdagradParameters | Retrieve Adagrad embedding parameters. |
| RetrieveTPUEmbeddingAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParameters |
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug | Retrieve Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingAdagradParametersGradAccumDebug |
| RetrieveTPUEmbeddingADAMParameters | Retrieve ADAM embedding parameters. |
| RetrieveTPUEmbeddingADAMParameters.Options | Optional attributes for RetrieveTPUEmbeddingADAMParameters |
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug | Retrieve ADAM embedding parameters with debug support. |
| RetrieveTPUEmbeddingADAMParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingADAMParametersGradAccumDebug |
| RetrieveTPUEmbeddingCenteredRMSPropParameters | Retrieve centered RMSProp embedding parameters. |
| RetrieveTPUEmbeddingCenteredRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingCenteredRMSPropParameters |
| RetrieveTPUEmbeddingFTRLParameters | Retrieve FTRL embedding parameters. |
| RetrieveTPUEmbeddingFTRLParameters.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParameters |
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug | Retrieve FTRL embedding parameters with debug support. |
| RetrieveTPUEmbeddingFTRLParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingFTRLParametersGradAccumDebug |
| RetrieveTPUEmbeddingMDLAdagradLightParameters | Retrieve MDL Adagrad Light embedding parameters. |
| RetrieveTPUEmbeddingMDLAdagradLightParameters.Options | Optional attributes for RetrieveTPUEmbeddingMDLAdagradLightParameters |
| RetrieveTPUEmbeddingMomentumParameters | Retrieve Momentum embedding parameters. |
| RetrieveTPUEmbeddingMomentumParameters.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParameters |
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug | Retrieve Momentum embedding parameters with debug support. |
| RetrieveTPUEmbeddingMomentumParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingMomentumParametersGradAccumDebug |
| RetrieveTPUEmbeddingProximalAdagradParameters | Retrieve proximal Adagrad embedding parameters. |
| RetrieveTPUEmbeddingProximalAdagradParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParameters |
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug | Retrieve proximal Adagrad embedding parameters with debug support. |
| RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug |
| RetrieveTPUEmbeddingProximalYogiParameters | |
| RetrieveTPUEmbeddingProximalYogiParameters.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParameters |
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug | |
| RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingProximalYogiParametersGradAccumDebug |
| RetrieveTPUEmbeddingRMSPropParameters | Retrieve RMSProp embedding parameters. |
| RetrieveTPUEmbeddingRMSPropParameters.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParameters |
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug | Retrieve RMSProp embedding parameters with debug support. |
| RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters | Retrieve SGD embedding parameters. |
| RetrieveTPUEmbeddingStochasticGradientDescentParameters.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParameters |
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug | Retrieve SGD embedding parameters with debug support. |
| RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug.Options | Optional attributes for RetrieveTPUEmbeddingStochasticGradientDescentParametersGradAccumDebug |
| Reverse <T extends TType > | Reverses specific dimensions of a tensor. |
| ReverseSequence <T extends TType > | Reverses variable length slices. |
| ReverseSequence.Options | Optional attributes for ReverseSequence |
| RewriterConfig | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.Builder | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
| RewriterConfig.CpuLayout | Enum for layout conversion between NCHW and NHWC on CPU. |
| RewriterConfig.CustomGraphOptimizer | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
| RewriterConfig.CustomGraphOptimizer.Builder | Message to describe custom graph optimizer and its parametersProtobuf type tensorflow.RewriterConfig.CustomGraphOptimizer |
| RewriterConfig.CustomGraphOptimizerOrBuilder | |
| RewriterConfig.MemOptType | Protobuf enum tensorflow.RewriterConfig.MemOptType |
| RewriterConfig.NumIterationsType | Enum controlling the number of times to run optimizers. |
| RewriterConfig.Toggle | Protobuf enum tensorflow.RewriterConfig.Toggle |
| RewriterConfigOrBuilder | |
| RewriterConfigProtos | |
| Rfft <U extends TType > | Real-valued fast Fourier transform. |
| Rfft2d <U extends TType > | 2D real-valued fast Fourier transform. |
| Rfft3d <U extends TType > | 3D real-valued fast Fourier transform. |
| RgbToHsv <T extends TNumber > | Converts one or more images from RGB to HSV. |
| RightShift <T extends TNumber > | Elementwise computes the bitwise right-shift of `x` and `y`. |
| Rint <T extends TNumber > | Returns element-wise integer closest to x. |
| RMSProp | Optimizer that implements the RMSProp algorithm. |
| RngReadAndSkip | Advance the counter of a counter-based RNG. |
| RngSkip | Advance the counter of a counter-based RNG. |
| Roll <T extends TType > | Rolls the elements of a tensor along an axis. |
| Round <T extends TType > | Rounds the values of a tensor to the nearest integer, element-wise. |
| Rpc | Perform batches of RPC requests. |
| Rpc.Options | Optional attributes for Rpc |
| RPCOptions | Protobuf type tensorflow.RPCOptions |
| RPCOptions.Builder | Protobuf type tensorflow.RPCOptions |
| RPCOptionsOrBuilder | |
| Rsqrt <T extends TType > | Computes reciprocal of square root of x element-wise. |
| RsqrtGrad <T extends TType > | Computes the gradient for the rsqrt of `x` wrt its input. |
| RunConfiguration | Run-specific items such as arguments to the test / benchmark. |
| RunConfiguration.Builder | Run-specific items such as arguments to the test / benchmark. |
| RunConfigurationOrBuilder | |
| RunMetadata | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.Builder | Metadata output (i.e., non-Tensor) for a single Run() call. |
| RunMetadata.FunctionGraphs | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
| RunMetadata.FunctionGraphs.Builder | Protobuf type tensorflow.RunMetadata.FunctionGraphs |
| RunMetadata.FunctionGraphsOrBuilder | |
| RunMetadataOrBuilder | |
| RunOptions | Options for a single Run() call. |
| RunOptions.Builder | Options for a single Run() call. |
| RunOptions.Experimental | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.Builder | Everything inside Experimental is subject to change and is not subject to API stability guarantees in https://www.tensorflow.org/guide/version_compat. |
| RunOptions.Experimental.RunHandlerPoolOptions | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptions.Builder | Options for run handler thread pool. |
| RunOptions.Experimental.RunHandlerPoolOptionsOrBuilder | |
| RunOptions.ExperimentalOrBuilder | |
| RunOptions.TraceLevel | TODO(pbar) Turn this into a TraceOptions proto which allows tracing to be controlled in a more orthogonal manner?Protobuf enum tensorflow.RunOptions.TraceLevel |
| RunOptionsOrBuilder |
S
| SampleDistortedBoundingBox <T extends TNumber > | Generate a single randomly distorted bounding box for an image. |
| SampleDistortedBoundingBox.Options | Optional attributes for SampleDistortedBoundingBox |
| SamplingDataset | Creates a dataset that takes a Bernoulli sample of the contents of another dataset. |
| Ahorrar | Saves tensors in V2 checkpoint format. |
| SaveableObject | Protobuf type tensorflow.SaveableObject |
| SaveableObject.Builder | Protobuf type tensorflow.SaveableObject |
| SaveableObjectOrBuilder | |
| SavedAsset | A SavedAsset points to an asset in the MetaGraph. |
| SavedAsset.Builder | A SavedAsset points to an asset in the MetaGraph. |
| SavedAssetOrBuilder | |
| SavedBareConcreteFunction | Protobuf type tensorflow.SavedBareConcreteFunction |
| SavedBareConcreteFunction.Builder | Protobuf type tensorflow.SavedBareConcreteFunction |
| SavedBareConcreteFunctionOrBuilder | |
| SavedConcreteFunction | Stores low-level information about a concrete function. |
| SavedConcreteFunction.Builder | Stores low-level information about a concrete function. |
| SavedConcreteFunctionOrBuilder | |
| SavedConstant | Protobuf type tensorflow.SavedConstant |
| SavedConstant.Builder | Protobuf type tensorflow.SavedConstant |
| SavedConstantOrBuilder | |
| SavedFunction | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunction.Builder | A function with multiple signatures, possibly with non-Tensor arguments. |
| SavedFunctionOrBuilder | |
| SavedModel | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModel.Builder | SavedModel is the high level serialization format for TensorFlow Models. |
| SavedModelBundle | SavedModelBundle represents a model loaded from storage. |
| SavedModelBundle.Exporter | Options for exporting a SavedModel. |
| SavedModelBundle.Loader | Options for loading a SavedModel. |
| SavedModelOrBuilder | |
| SavedModelProtos | |
| SavedObject | Protobuf type tensorflow.SavedObject |
| SavedObject.Builder | Protobuf type tensorflow.SavedObject |
| SavedObject.KindCase | |
| SavedObjectGraph | Protobuf type tensorflow.SavedObjectGraph |
| SavedObjectGraph.Builder | Protobuf type tensorflow.SavedObjectGraph |
| SavedObjectGraphOrBuilder | |
| SavedObjectGraphProtos | |
| SavedObjectOrBuilder | |
| SavedResource | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResource.Builder | A SavedResource represents a TF object that holds state during its lifetime. |
| SavedResourceOrBuilder | |
| SavedSlice | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSlice.Builder | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
| SavedSliceMeta | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMeta.Builder | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
| SavedSliceMetaOrBuilder | |
| SavedSliceOrBuilder | |
| SavedTensorSliceMeta | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMeta.Builder | Metadata describing the set of tensor slices saved in a checkpoint file. |
| SavedTensorSliceMetaOrBuilder | |
| SavedTensorSliceProtos | |
| SavedTensorSlices | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlices.Builder | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
| SavedTensorSlicesOrBuilder | |
| SavedUserObject | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObject.Builder | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
| SavedUserObjectOrBuilder | |
| SavedVariable | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariable.Builder | Represents a Variable that is initialized by loading the contents from the checkpoint. |
| SavedVariableOrBuilder | |
| SaverDef | Protocol buffer representing the configuration of a Saver. |
| SaverDef.Builder | Protocol buffer representing the configuration of a Saver. |
| SaverDef.CheckpointFormatVersion | A version number that identifies a different on-disk checkpoint format. |
| SaverDefOrBuilder | |
| SaverProtos | |
| SaveSliceInfoDef | Protobuf type tensorflow.SaveSliceInfoDef |
| SaveSliceInfoDef.Builder | Protobuf type tensorflow.SaveSliceInfoDef |
| SaveSliceInfoDefOrBuilder | |
| SaveSlices | Saves input tensors slices to disk. |
| ScalarSummary | Outputs a `Summary` protocol buffer with scalar values. |
| ScaleAndTranslate | |
| ScaleAndTranslate.Options | Optional attributes for ScaleAndTranslate |
| ScaleAndTranslateGrad <T extends TNumber > | |
| ScaleAndTranslateGrad.Options | Optional attributes for ScaleAndTranslateGrad |
| ScatterAdd <T extends TType > | Adds sparse updates to a variable reference. |
| ScatterAdd.Options | Optional attributes for ScatterAdd |
| ScatterDiv <T extends TType > | Divides a variable reference by sparse updates. |
| ScatterDiv.Options | Optional attributes for ScatterDiv |
| ScatterMax <T extends TNumber > | Reduces sparse updates into a variable reference using the `max` operation. |
| ScatterMax.Options | Optional attributes for ScatterMax |
| ScatterMin <T extends TNumber > | Reduces sparse updates into a variable reference using the `min` operation. |
| ScatterMin.Options | Optional attributes for ScatterMin |
| ScatterMul <T extends TType > | Multiplies sparse updates into a variable reference. |
| ScatterMul.Options | Optional attributes for ScatterMul |
| ScatterNd <U extends TType > | Scatter `updates` into a new tensor according to `indices`. |
| ScatterNdAdd <T extends TType > | Applies sparse addition to individual values or slices in a Variable. |
| ScatterNdAdd.Options | Optional attributes for ScatterNdAdd |
| ScatterNdMax <T extends TType > | Computes element-wise maximum. |
| ScatterNdMax.Options | Optional attributes for ScatterNdMax |
| ScatterNdMin <T extends TType > | Computes element-wise minimum. |
| ScatterNdMin.Options | Optional attributes for ScatterNdMin |
| ScatterNdNonAliasingAdd <T extends TType > | Applies sparse addition to `input` using individual values or slices from `updates` according to indices `indices`. |
| ScatterNdSub <T extends TType > | Applies sparse subtraction to individual values or slices in a Variable. |
| ScatterNdSub.Options | Optional attributes for ScatterNdSub |
| ScatterNdUpdate <T extends TType > | Applies sparse `updates` to individual values or slices within a given variable according to `indices`. |
| ScatterNdUpdate.Options | Optional attributes for ScatterNdUpdate |
| ScatterSub <T extends TType > | Subtracts sparse updates to a variable reference. |
| ScatterSub.Options | Optional attributes for ScatterSub |
| ScatterUpdate <T extends TType > | Applies sparse updates to a variable reference. |
| ScatterUpdate.Options | Optional attributes for ScatterUpdate |
| Alcance | Manages groups of related properties when creating Tensorflow Operations, such as a common name prefix. |
| ScopedAllocatorOptions | Protobuf type tensorflow.ScopedAllocatorOptions |
| ScopedAllocatorOptions.Builder | Protobuf type tensorflow.ScopedAllocatorOptions |
| ScopedAllocatorOptionsOrBuilder | |
| SdcaFprint | Computes fingerprints of the input strings. |
| SdcaOptimizer | Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for linear models with L1 + L2 regularization. |
| SdcaOptimizer.Options | Optional attributes for SdcaOptimizer |
| SdcaShrinkL1 | Applies L1 regularization shrink step on the parameters. |
| SegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
| SegmentMean <T extends TType > | Computes the mean along segments of a tensor. |
| SegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
| SegmentProd <T extends TType > | Computes the product along segments of a tensor. |
| SegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
| Select <T extends TType > | |
| SelfAdjointEig <T extends TType > | Computes the eigen decomposition of one or more square self-adjoint matrices. |
| SelfAdjointEig <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
| SelfAdjointEig.Options | Optional attributes for SelfAdjointEig |
| Selu <T extends TNumber > | Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)` if < 0, `scale * features` otherwise. |
| SELU <T extends TFloating > | Scaled Exponential Linear Unit (SELU). |
| SeluGrad <T extends TNumber > | Computes gradients for the scaled exponential linear (Selu) operation. |
| Enviar | Sends the named tensor from send_device to recv_device. |
| Enviar | Sends the named tensor to another XLA computation. |
| Send.Options | Optional attributes for Send |
| SendTPUEmbeddingGradients | Performs gradient updates of embedding tables. |
| SequenceExample | Protobuf type tensorflow.SequenceExample |
| SequenceExample.Builder | Protobuf type tensorflow.SequenceExample |
| SequenceExampleOrBuilder | |
| SerializeIterator | Converts the given `resource_handle` representing an iterator to a variant tensor. |
| SerializeIterator.Options | Optional attributes for SerializeIterator |
| SerializeManySparse <U extends TType > | Serialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object. |
| SerializeSparse <U extends TType > | Serialize a `SparseTensor` into a `[3]` `Tensor` object. |
| SerializeTensor | Transforms a Tensor into a serialized TensorProto proto. |
| Servidor | An in-process TensorFlow server, for use in distributed training. |
| ServerDef | Defines the configuration of a single TensorFlow server. |
| ServerDef.Builder | Defines the configuration of a single TensorFlow server. |
| ServerDefOrBuilder | |
| ServerProtos | |
| ServiceConfig | |
| ServiceConfig.DispatcherConfig | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfig.Builder | Configuration for a tf.data service DispatchServer. |
| ServiceConfig.DispatcherConfigOrBuilder | |
| ServiceConfig.WorkerConfig | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfig.Builder | Configuration for a tf.data service WorkerServer. |
| ServiceConfig.WorkerConfigOrBuilder | |
| Sesión | Driver for Graph execution. |
| Session.Run | Output tensors and metadata obtained when executing a session. |
| Session.Runner | Run Operation s and evaluate Tensors . |
| SessionLog | Protocol buffer used for logging session state. |
| SessionLog.Builder | Protocol buffer used for logging session state. |
| SessionLog.SessionStatus | Protobuf enum tensorflow.SessionLog.SessionStatus |
| SessionLogOrBuilder | |
| SessionMetadata | Metadata about the session. |
| SessionMetadata.Builder | Metadata about the session. |
| SessionMetadataOrBuilder | |
| SetDiff1d <T extends TType , U extends TNumber > | Computes the difference between two lists of numbers or strings. |
| SetSize | Number of unique elements along last dimension of input `set`. |
| SetSize.Options | Optional attributes for SetSize |
| SetsOps | Implementation of set operations |
| SetsOps.Operation | Enumeration containing the string operation values to be passed to the TensorFlow Sparse Ops function ERROR(/SparseOps#denseToDenseSetOperation) |
| SetStatsAggregatorDataset | |
| SetStatsAggregatorDataset | |
| Forma | The shape of a Tensor or NdArray . |
| Shape <U extends TNumber > | Returns the shape of a tensor. |
| Shape_inference_func_TF_ShapeInferenceContext_TF_Status | |
| Conformado | Any data container with a given Shape . |
| ShapeN <U extends TNumber > | Returns shape of tensors. |
| formas | An operator providing methods on org.tensorflow.op.core.Shape tensors and 1d operands that represent the dimensions of a shape. |
| ShapeUtils | Various methods for processing with Shapes and Operands |
| ShardDataset | Creates a `Dataset` that includes only 1/`num_shards` of this dataset. |
| ShardDataset.Options | Optional attributes for ShardDataset |
| ShardedFilename | Generate a sharded filename. |
| ShardedFilespec | Generate a glob pattern matching all sharded file names. |
| Sharding <T extends TType > | An op which shards the input based on the given sharding attribute. |
| ShortDataBuffer | A DataBuffer of shorts. |
| ShortDataLayout <S extends DataBuffer <?>> | A DataLayout that converts data stored in a buffer to shorts. |
| ShortDenseNdArray | |
| ShortNdArray | An NdArray of shorts. |
| ShuffleAndRepeatDataset | |
| ShuffleAndRepeatDataset.Options | Optional attributes for ShuffleAndRepeatDataset |
| ShuffleDataset | |
| ShuffleDataset.Options | Optional attributes for ShuffleDataset |
| ShutdownDistributedTPU | Shuts down a running distributed TPU system. |
| Sigmoid <T extends TFloating > | Sigmoid activation. |
| Sigmoid <T extends TType > | Computes sigmoid of `x` element-wise. |
| SigmoidCrossEntropyWithLogits | |
| SigmoidGrad <T extends TType > | Computes the gradient of the sigmoid of `x` wrt its input. |
| Sign <T extends TType > | Returns an element-wise indication of the sign of a number. |
| Firma | Describe the inputs and outputs of an executable entity, such as a ConcreteFunction , among other useful metadata. |
| Signature.Builder | Builds a new function signature. |
| Signature.TensorDescription | |
| SignatureDef | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDef.Builder | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
| SignatureDefOrBuilder | |
| Sin <T extends TType > | Computes sine of x element-wise. |
| SingleElementSequence <T, U extends NdArray <T>> | A sequence of one single element |
| Sinh <T extends TType > | Computes hyperbolic sine of x element-wise. |
| Size <U extends TNumber > | Returns the size of a tensor. |
| SkipDataset | |
| SkipDataset | Creates a dataset that skips `count` elements from the `input_dataset`. |
| Skipgram | Parses a text file and creates a batch of examples. |
| Skipgram.Options | Optional attributes for Skipgram |
| SleepDataset | |
| SleepDataset | |
| Slice <T extends TType > | Return a slice from 'input'. |
| SlicingElementSequence <T, U extends NdArray <T>> | A sequence creating a new NdArray instance (slice) for each element of an iteration |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| SlidingWindowDataset | Creates a dataset that passes a sliding window over `input_dataset`. |
| Snapshot <T extends TType > | Returns a copy of the input tensor. |
| Instantánea | Protobuf type tensorflow.SnapShot |
| SnapShot.Builder | Protobuf type tensorflow.SnapShot |
| SnapshotMetadataRecord | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecord.Builder | This stores the metadata information present in each snapshot record. |
| SnapshotMetadataRecordOrBuilder | |
| SnapShotOrBuilder | |
| SnapshotProtos | |
| SnapshotRecord | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecord.Builder | Each SnapshotRecord represents one batch of pre-processed input data. |
| SnapshotRecordOrBuilder | |
| SnapshotTensorMetadata | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadata.Builder | Metadata for all the tensors in a Snapshot Record. |
| SnapshotTensorMetadataOrBuilder | |
| SobolSample <T extends TNumber > | Generates points from the Sobol sequence. |
| Softmax <T extends TFloating > | Softmax converts a real vector to a vector of categorical probabilities. |
| Softmax <T extends TNumber > | Computes softmax activations. |
| SoftmaxCrossEntropyWithLogits | |
| SoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
| Softplus <T extends TFloating > | Softplus activation function, softplus(x) = log(exp(x) + 1) . |
| Softplus <T extends TNumber > | Computes softplus: `log(exp(features) + 1)`. |
| SoftplusGrad <T extends TNumber > | Computes softplus gradients for a softplus operation. |
| Softsign <T extends TFloating > | Softsign activation function, softsign(x) = x / (abs(x) + 1) . |
| Softsign <T extends TNumber > | Computes softsign: `features / (abs(features) + 1)`. |
| SoftsignGrad <T extends TNumber > | Computes softsign gradients for a softsign operation. |
| Solve <T extends TType > | Solves systems of linear equations. |
| Solve.Options | Optional attributes for Solve |
| Sort <T extends TType > | Wraps the XLA Sort operator, documented at https://www.tensorflow.org/performance/xla/operation_semantics#sort . |
| SourceFile | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFile.Builder | Content of a source file involved in the execution of the debugged TensorFlow program. |
| SourceFileOrBuilder | |
| SpaceToBatch <T extends TType > | SpaceToBatch for 4-D tensors of type T. |
| SpaceToBatchNd <T extends TType > | SpaceToBatch for ND tensors of type T. |
| SpaceToDepth <T extends TType > | SpaceToDepth for tensors of type T. |
| SpaceToDepth.Options | Optional attributes for SpaceToDepth |
| SparseAccumulatorApplyGradient | Applies a sparse gradient to a given accumulator. |
| SparseAccumulatorTakeGradient <T extends TType > | Extracts the average sparse gradient in a SparseConditionalAccumulator. |
| SparseAdd <T extends TType > | Adds two `SparseTensor` objects to produce another `SparseTensor`. |
| SparseAddGrad <T extends TType > | The gradient operator for the SparseAdd op. |
| SparseApplyAdadelta <T extends TType > | var: Should be from a Variable(). |
| SparseApplyAdadelta.Options | Optional attributes for SparseApplyAdadelta |
| SparseApplyAdagrad <T extends TType > | Update relevant entries in '*var' and '*accum' according to the adagrad scheme. |
| SparseApplyAdagrad.Options | Optional attributes for SparseApplyAdagrad |
| SparseApplyAdagradDa <T extends TType > | Update entries in '*var' and '*accum' according to the proximal adagrad scheme. |
| SparseApplyAdagradDa.Options | Optional attributes for SparseApplyAdagradDa |
| SparseApplyCenteredRmsProp <T extends TType > | Update '*var' according to the centered RMSProp algorithm. |
| SparseApplyCenteredRmsProp.Options | Optional attributes for SparseApplyCenteredRmsProp |
| SparseApplyFtrl <T extends TType > | Update relevant entries in '*var' according to the Ftrl-proximal scheme. |
| SparseApplyFtrl.Options | Optional attributes for SparseApplyFtrl |
| SparseApplyMomentum <T extends TType > | Update relevant entries in '*var' and '*accum' according to the momentum scheme. |
| SparseApplyMomentum.Options | Optional attributes for SparseApplyMomentum |
| SparseApplyProximalAdagrad <T extends TType > | Sparse update entries in '*var' and '*accum' according to FOBOS algorithm. |
| SparseApplyProximalAdagrad.Options | Optional attributes for SparseApplyProximalAdagrad |
| SparseApplyProximalGradientDescent <T extends TType > | Sparse update '*var' as FOBOS algorithm with fixed learning rate. |
| SparseApplyProximalGradientDescent.Options | Optional attributes for SparseApplyProximalGradientDescent |
| SparseApplyRmsProp <T extends TType > | Update '*var' according to the RMSProp algorithm. |
| SparseApplyRmsProp.Options | Optional attributes for SparseApplyRmsProp |
| SparseBincount <U extends TNumber > | Counts the number of occurrences of each value in an integer array. |
| SparseBincount.Options | Optional attributes for SparseBincount |
| SparseCategoricalCrossentropy | Computes the crossentropy loss between labels and predictions. |
| SparseCategoricalCrossentropy <T extends TNumber > | A metric that computes the sparse categorical cross-entropy loss between true labels and predicted labels. |
| SparseConcat <T extends TType > | Concatenates a list of `SparseTensor` along the specified dimension. |
| SparseConditionalAccumulator | A conditional accumulator for aggregating sparse gradients. |
| SparseConditionalAccumulator.Options | Optional attributes for SparseConditionalAccumulator |
| SparseCountSparseOutput <U extends TNumber > | Performs sparse-output bin counting for a sparse tensor input. |
| SparseCountSparseOutput.Options | Optional attributes for SparseCountSparseOutput |
| SparseCross | Generates sparse cross from a list of sparse and dense tensors. |
| SparseCrossHashed | Generates sparse cross from a list of sparse and dense tensors. |
| SparseDenseCwiseAdd <T extends TType > | Adds up a SparseTensor and a dense Tensor, using these special rules: (1) Broadcasts the dense side to have the same shape as the sparse side, if eligible; (2) Then, only the dense values pointed to by the indices of the SparseTensor participate in the cwise addition. |
| SparseDenseCwiseDiv <T extends TType > | Component-wise divides a SparseTensor by a dense Tensor. |
| SparseDenseCwiseMul <T extends TType > | Component-wise multiplies a SparseTensor by a dense Tensor. |
| SparseFillEmptyRows <T extends TType > | Fills empty rows in the input 2-D `SparseTensor` with a default value. |
| SparseFillEmptyRowsGrad <T extends TType > | The gradient of SparseFillEmptyRows. |
| SparseMatMul | Multiply matrix "a" by matrix "b". |
| SparseMatMul.Options | Optional attributes for SparseMatMul |
| SparseMatrixAdd | Sparse addition of two CSR matrices, C = alpha * A + beta * B. |
| SparseMatrixMatMul <T extends TType > | Matrix-multiplies a sparse matrix with a dense matrix. |
| SparseMatrixMatMul.Options | Optional attributes for SparseMatrixMatMul |
| SparseMatrixMul | Element-wise multiplication of a sparse matrix with a dense tensor. |
| SparseMatrixNNZ | Returns the number of nonzeroes of `sparse_matrix`. |
| SparseMatrixOrderingAMD | Computes the Approximate Minimum Degree (AMD) ordering of `input`. |
| SparseMatrixSoftmax | Calculates the softmax of a CSRSparseMatrix. |
| SparseMatrixSoftmaxGrad | Calculates the gradient of the SparseMatrixSoftmax op. |
| SparseMatrixSparseCholesky | Computes the sparse Cholesky decomposition of `input`. |
| SparseMatrixSparseMatMul | Sparse-matrix-multiplies two CSR matrices `a` and `b`. |
| SparseMatrixSparseMatMul.Options | Optional attributes for SparseMatrixSparseMatMul |
| SparseMatrixTranspose | Transposes the inner (matrix) dimensions of a CSRSparseMatrix. |
| SparseMatrixTranspose.Options | Optional attributes for SparseMatrixTranspose |
| SparseMatrixZeros | Creates an all-zeros CSRSparseMatrix with shape `dense_shape`. |
| SparseReduceMax <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMax.Options | Optional attributes for SparseReduceMax |
| SparseReduceMaxSparse <T extends TNumber > | Computes the max of elements across dimensions of a SparseTensor. |
| SparseReduceMaxSparse.Options | Optional attributes for SparseReduceMaxSparse |
| SparseReduceSum <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSum.Options | Optional attributes for SparseReduceSum |
| SparseReduceSumSparse <T extends TType > | Computes the sum of elements across dimensions of a SparseTensor. |
| SparseReduceSumSparse.Options | Optional attributes for SparseReduceSumSparse |
| SparseReorder <T extends TType > | Reorders a SparseTensor into the canonical, row-major ordering. |
| SparseReshape | Reshapes a SparseTensor to represent values in a new dense shape. |
| SparseSegmentMean <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
| SparseSegmentMeanGrad <T extends TNumber > | Computes gradients for SparseSegmentMean. |
| SparseSegmentMeanWithNumSegments <T extends TNumber > | Computes the mean along sparse segments of a tensor. |
| SparseSegmentSqrtN <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSqrtNGrad <T extends TNumber > | Computes gradients for SparseSegmentSqrtN. |
| SparseSegmentSqrtNWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor divided by the sqrt of N. |
| SparseSegmentSum <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
| SparseSegmentSumWithNumSegments <T extends TNumber > | Computes the sum along sparse segments of a tensor. |
| SparseSlice <T extends TType > | Slice a `SparseTensor` based on the `start` and `size`. |
| SparseSliceGrad <T extends TType > | The gradient operator for the SparseSlice op. |
| SparseSoftmax <T extends TNumber > | Applies softmax to a batched ND `SparseTensor`. |
| SparseSoftmaxCrossEntropyWithLogits | |
| SparseSoftmaxCrossEntropyWithLogits <T extends TNumber > | Computes softmax cross entropy cost and gradients to backpropagate. |
| SparseSparseMaximum <T extends TNumber > | Returns the element-wise max of two SparseTensors. |
| SparseSparseMinimum <T extends TType > | Returns the element-wise min of two SparseTensors. |
| SparseSplit <T extends TType > | Split a `SparseTensor` into `num_split` tensors along one dimension. |
| SparseTensorDenseAdd <U extends TType > | Adds up a `SparseTensor` and a dense `Tensor`, producing a dense `Tensor`. |
| SparseTensorDenseMatMul <U extends TType > | Multiply SparseTensor (of rank 2) "A" by dense matrix "B". |
| SparseTensorDenseMatMul.Options | Optional attributes for SparseTensorDenseMatMul |
| SparseTensorSliceDataset | Creates a dataset that splits a SparseTensor into elements row-wise. |
| SparseTensorToCSRSparseMatrix | Converts a SparseTensor to a (possibly batched) CSRSparseMatrix. |
| SparseToDense <U extends TType > | Converts a sparse representation into a dense tensor. |
| SparseToDense.Options | Optional attributes for SparseToDense |
| SparseToSparseSetOperation <T extends TType > | Applies set operation along last dimension of 2 `SparseTensor` inputs. |
| SparseToSparseSetOperation.Options | Optional attributes for SparseToSparseSetOperation |
| SpecializedType | For identifying the underlying type of a variant. |
| Spence <T extends TNumber > | |
| Split <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
| SplitV <T extends TType > | Splits a tensor into `num_split` tensors along one dimension. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| SqlDataset | Creates a dataset that executes a SQL query and emits rows of the result set. |
| Sqrt <T extends TType > | Computes square root of x element-wise. |
| SqrtGrad <T extends TType > | Computes the gradient for the sqrt of `x` wrt its input. |
| Sqrtm <T extends TType > | Computes the matrix square root of one or more square matrices: matmul(sqrtm(A), sqrtm(A)) = A The input matrix should be invertible. |
| Square <T extends TType > | Computes square of x element-wise. |
| SquaredDifference <T extends TType > | Returns conj(x - y)(x - y) element-wise. |
| SquaredHinge | Computes the squared hinge loss between labels and predictions. |
| SquaredHinge <T extends TNumber > | A metric that computes the squared hinge loss metric between labels and predictions. |
| Squeeze <T extends TType > | Removes dimensions of size 1 from the shape of a tensor. |
| Squeeze.Options | Optional attributes for Squeeze |
| Stack <T extends TType > | Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor. |
| Stack.Options | Optional attributes for Stack |
| StackFrameWithId | A stack frame with ID. |
| StackFrameWithId.Builder | A stack frame with ID. |
| StackFrameWithIdOrBuilder | |
| Escenario | Stage values similar to a lightweight Enqueue. |
| Stage.Options | Optional attributes for Stage |
| StageClear | Op removes all elements in the underlying container. |
| StageClear.Options | Optional attributes for StageClear |
| StagePeek | Op peeks at the values at the specified index. |
| StagePeek.Options | Optional attributes for StagePeek |
| StageSize | Op returns the number of elements in the underlying container. |
| StageSize.Options | Optional attributes for StageSize |
| StatefulRandomBinomial <V extends TNumber > | |
| StatefulStandardNormal <U extends TType > | Outputs random values from a normal distribution. |
| StatefulTruncatedNormal <U extends TType > | Outputs random values from a truncated normal distribution. |
| StatefulUniform <U extends TType > | Outputs random values from a uniform distribution. |
| StatefulUniformFullInt <U extends TType > | Outputs random integers from a uniform distribution. |
| StatefulUniformInt <U extends TType > | Outputs random integers from a uniform distribution. |
| StatelessMultinomial <V extends TNumber > | Draws samples from a multinomial distribution. |
| StatelessParameterizedTruncatedNormal <V extends TNumber > | |
| StatelessRandomBinomial <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a binomial distribution. |
| StatelessRandomGamma <V extends TNumber > | Outputs deterministic pseudorandom random numbers from a gamma distribution. |
| StatelessRandomGetKeyCounterAlg | Picks the best algorithm based on device, and scrambles seed into key and counter. |
| StatelessRandomNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a normal distribution. |
| StatelessRandomPoisson <W extends TNumber > | Outputs deterministic pseudorandom random numbers from a Poisson distribution. |
| StatelessRandomUniform <V extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessRandomUniformFullInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformFullIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformInt <V extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformIntV2 <U extends TNumber > | Outputs deterministic pseudorandom random integers from a uniform distribution. |
| StatelessRandomUniformV2 <U extends TNumber > | Outputs deterministic pseudorandom random values from a uniform distribution. |
| StatelessSampleDistortedBoundingBox <T extends TNumber > | Generate a randomly distorted bounding box for an image deterministically. |
| StatelessSampleDistortedBoundingBox.Options | Optional attributes for StatelessSampleDistortedBoundingBox |
| StatelessTruncatedNormal <V extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StatelessTruncatedNormalV2 <U extends TNumber > | Outputs deterministic pseudorandom values from a truncated normal distribution. |
| StaticRegexFullMatch | Check if the input matches the regex pattern. |
| StaticRegexReplace | Replaces the match of pattern in input with rewrite. |
| StaticRegexReplace.Options | Optional attributes for StaticRegexReplace |
| StatsAggregatorHandle | Creates a statistics manager resource. |
| StatsAggregatorHandle | |
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
| StatsAggregatorHandle.Options | Optional attributes for StatsAggregatorHandle |
| StatsAggregatorSetSummaryWriter | Set a summary_writer_interface to record statistics using given stats_aggregator. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StatsAggregatorSummary | Produces a summary of any statistics recorded by the given statistics manager. |
| StdArrays | Utility class for working with NdArray instances mixed with standard Java arrays. |
| StepStats | Protobuf type tensorflow.StepStats |
| StepStats.Builder | Protobuf type tensorflow.StepStats |
| StepStatsOrBuilder | |
| StepStatsProtos | |
| StopGradient <T extends TType > | Stops gradient computation. |
| StridedSlice <T extends TType > | Return a strided slice from `input`. |
| StridedSlice.Options | Optional attributes for StridedSlice |
| StridedSliceAssign <T extends TType > | Assign `value` to the sliced l-value reference of `ref`. |
| StridedSliceAssign.Options | Optional attributes for StridedSliceAssign |
| StridedSliceGrad <U extends TType > | Returns the gradient of `StridedSlice`. |
| StridedSliceGrad.Options | Optional attributes for StridedSliceGrad |
| StridedSliceHelper | Helper endpoint methods for Python like indexing. |
| StringFormat | Formats a string template using a list of tensors. |
| StringFormat.Options | Optional attributes for StringFormat |
| StringLayout | Data layout that converts a String to/from a sequence of bytes applying a given charset. |
| StringLength | String lengths of `input`. |
| StringLength.Options | Optional attributes for StringLength |
| StringNGrams <T extends TNumber > | Creates ngrams from ragged string data. |
| StringSplit | Split elements of `source` based on `sep` into a `SparseTensor`. |
| StringSplit.Options | Optional attributes for StringSplit |
| Banda | Strip leading and trailing whitespaces from the Tensor. |
| StructProtos | |
| StructuredValue | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.Builder | `StructuredValue` represents a dynamically typed value representing various data structures that are inspired by Python data structures typically used in TensorFlow functions as inputs and outputs. |
| StructuredValue.KindCase | |
| StructuredValueOrBuilder | |
| Sub <T extends TType > | Returns x - y element-wise. |
| substrato | Return substrings from `Tensor` of strings. |
| Substr.Options | Optional attributes for Substr |
| Sum <T extends TType > | Computes the sum of elements across dimensions of a tensor. |
| Sum.Options | Optional attributes for Sum |
| Resumen | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Audio | Protobuf type tensorflow.Summary.Audio |
| Summary.Audio.Builder | Protobuf type tensorflow.Summary.Audio |
| Summary.AudioOrBuilder | |
| Summary.Builder | A Summary is a set of named values to be displayed by the visualizer. |
| Summary.Image | Protobuf type tensorflow.Summary.Image |
| Summary.Image.Builder | Protobuf type tensorflow.Summary.Image |
| Summary.ImageOrBuilder | |
| Summary.Value | Protobuf type tensorflow.Summary.Value |
| Summary.Value.Builder | Protobuf type tensorflow.Summary.Value |
| Summary.Value.ValueCase | |
| Summary.ValueOrBuilder | |
| SummaryDescription | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
| SummaryDescription.Builder | Metadata associated with a series of Summary dataProtobuf type tensorflow.SummaryDescription |
| SummaryDescriptionOrBuilder | |
| SummaryMetadata | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.Builder | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
| SummaryMetadata.PluginData | Protobuf type tensorflow.SummaryMetadata.PluginData |
| SummaryMetadata.PluginData.Builder | Protobuf type tensorflow.SummaryMetadata.PluginData |
| SummaryMetadata.PluginDataOrBuilder | |
| SummaryMetadataOrBuilder | |
| SummaryOrBuilder | |
| SummaryProtos | |
| SummaryWriter | |
| SummaryWriter.Options | Optional attributes for SummaryWriter |
| Svd <T extends TType > | Computes the singular value decompositions of one or more matrices. |
| Svd <T extends TType > | Computes the eigen decomposition of a batch of self-adjoint matrices (Note: Only real inputs are supported). |
| Svd.Options | Optional attributes for Svd |
| Swish <T extends TFloating > | Swish activation function. |
| SwitchCond <T extends TType > | Forwards `data` to the output port determined by `pred`. |
t
| TaggedRunMetadata | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadata.Builder | For logging the metadata output for a single session.run() call. |
| TaggedRunMetadataOrBuilder | |
| TakeDataset | |
| TakeDataset | Creates a dataset that contains `count` elements from the `input_dataset`. |
| TakeManySparseFromTensorsMap <T extends TType > | Read `SparseTensors` from a `SparseTensorsMap` and concatenate them. |
| TakeManySparseFromTensorsMap.Options | Optional attributes for TakeManySparseFromTensorsMap |
| Tan <T extends TType > | Computes tan of x element-wise. |
| Tanh <T extends TFloating > | Hyperbolic tangent activation function. |
| Tanh <T extends TType > | Computes hyperbolic tangent of `x` element-wise. |
| TanhGrad <T extends TType > | Computes the gradient for the tanh of `x` wrt its input. |
| TaskDeviceFilters | Defines the device filters for a remote task. |
| TaskDeviceFilters.Builder | Defines the device filters for a remote task. |
| TaskDeviceFiltersOrBuilder | |
| TBfloat16 | Brain 16-bit float tensor type. |
| TBfloat16Mapper | Maps memory of DT_BFLOAT16 tensors to a n-dimensional data space. |
| TBool | Boolean tensor type. |
| TBoolMapper | Maps memory of DT_BOOL tensors to a n-dimensional data space. |
| TemporaryVariable <T extends TType > | Returns a tensor that may be mutated, but only persists within a single step. |
| TemporaryVariable.Options | Optional attributes for TemporaryVariable |
| Tensor | A statically typed multi-dimensional array. |
| Tensor | |
| TensorArray | An array of Tensors of given size. |
| TensorArray.Options | Optional attributes for TensorArray |
| TensorArrayClose | Delete the TensorArray from its resource container. |
| TensorArrayConcat <T extends TType > | Concat the elements from the TensorArray into value `value`. |
| TensorArrayConcat.Options | Optional attributes for TensorArrayConcat |
| TensorArrayGather <T extends TType > | Gather specific elements from the TensorArray into output `value`. |
| TensorArrayGather.Options | Optional attributes for TensorArrayGather |
| TensorArrayGrad | Creates a TensorArray for storing the gradients of values in the given handle. |
| TensorArrayGradWithShape | Creates a TensorArray for storing multiple gradients of values in the given handle. |
| TensorArrayPack <T extends TType > | |
| TensorArrayPack.Options | Optional attributes for TensorArrayPack |
| TensorArrayRead <T extends TType > | Read an element from the TensorArray into output `value`. |
| TensorArrayScatter | Scatter the data from the input value into specific TensorArray elements. |
| TensorArraySize | Get the current size of the TensorArray. |
| TensorArraySplit | Split the data from the input value into TensorArray elements. |
| TensorArrayUnpack | |
| TensorArrayWrite | Push an element onto the tensor_array. |
| TensorBuffers | Maps native tensor memory into DataBuffers , allowing I/O operations from the JVM. |
| TensorBundleProtos | |
| TensorConnection | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnection.Builder | Defines a connection between two tensors in a `GraphDef`. |
| TensorConnectionOrBuilder | |
| TensorDataset | Creates a dataset that emits `components` as a tuple of tensors once. |
| TensorDebugMode | Available modes for extracting debugging information from a Tensor. |
| TensorDescription | Protobuf type tensorflow.TensorDescription |
| TensorDescription.Builder | Protobuf type tensorflow.TensorDescription |
| TensorDescriptionOrBuilder | |
| TensorDescriptionProtos | |
| TensorDiag <T extends TType > | Returns a diagonal tensor with a given diagonal values. |
| TensorDiagPart <T extends TType > | Returns the diagonal part of the tensor. |
| TensorFlow | Static utility methods describing the TensorFlow runtime. |
| flujo tensor | |
| flujo tensor | |
| TensorFlowException | Unchecked exception thrown by TensorFlow core classes |
| TensorForestCreateTreeVariable | Creates a tree resource and returns a handle to it. |
| TensorForestTreeDeserialize | Deserializes a proto into the tree handle |
| TensorForestTreeIsInitializedOp | Checks whether a tree has been initialized. |
| TensorForestTreePredict | Output the logits for the given input data |
| TensorForestTreeResourceHandleOp | Creates a handle to a TensorForestTreeResource |
| TensorForestTreeResourceHandleOp.Options | Optional attributes for TensorForestTreeResourceHandleOp |
| TensorForestTreeSerialize | Serializes the tree handle to a proto |
| TensorForestTreeSize | Get the number of nodes in a tree |
| TensorInfo | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.Builder | Information about a Tensor necessary for feeding or retrieval. |
| TensorInfo.CompositeTensor | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensor.Builder | Generic encoding for composite tensors. |
| TensorInfo.CompositeTensorOrBuilder | |
| TensorInfo.CooSparse | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparse.Builder | For sparse tensors, The COO encoding stores a triple of values, indices, and shape. |
| TensorInfo.CooSparseOrBuilder | |
| TensorInfo.EncodingCase | |
| TensorInfoOrBuilder | |
| TensorListConcat <U extends TType > | Concats all tensors in the list along the 0th dimension. |
| TensorListConcatLists | |
| TensorListElementShape <T extends TNumber > | The shape of the elements of the given list, as a tensor. |
| TensorListFromTensor | Creates a TensorList which, when stacked, has the value of `tensor`. |
| TensorListGather <T extends TType > | Creates a Tensor by indexing into the TensorList. |
| TensorListGetItem <T extends TType > | |
| TensorListLength | Returns the number of tensors in the input tensor list. |
| TensorListPopBack <T extends TType > | Returns the last element of the input list as well as a list with all but that element. |
| TensorListPushBack | Returns a list which has the passed-in `Tensor` as last element and the other elements of the given list in `input_handle`. |
| TensorListPushBackBatch | |
| TensorListReserve | List of the given size with empty elements. |
| TensorListResize | Resizes the list. |
| TensorListScatter | Creates a TensorList by indexing into a Tensor. |
| TensorListScatterIntoExistingList | Scatters tensor at indices in an input list. |
| TensorListSetItem | |
| TensorListSplit | Splits a tensor into a list. |
| TensorListStack <T extends TType > | Stacks all tensors in the list. |
| TensorListStack.Options | Optional attributes for TensorListStack |
| TensorMapErase | Returns a tensor map with item from given key erased. |
| TensorMapHasKey | Returns whether the given key exists in the map. |
| TensorMapInsert | Returns a map that is the 'input_handle' with the given key-value pair inserted. |
| TensorMapLookup <U extends TType > | Returns the value from a given key in a tensor map. |
| TensorMapper <T extends TType > | Maps the native memory of a RawTensor to a n-dimensional typed data space accessible from the JVM. |
| TensorMapSize | Returns the number of tensors in the input tensor map. |
| TensorMapStackKeys <T extends TType > | Returns a Tensor stack of all keys in a tensor map. |
| TensorMetadata | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadata.Builder | Metadata for a single tensor in the Snapshot Record. |
| TensorMetadataOrBuilder | |
| TensorProto | Protocol buffer representing a tensor. |
| TensorProto.Builder | Protocol buffer representing a tensor. |
| TensorProtoOrBuilder | |
| TensorProtos | |
| TensorScatterNdAdd <T extends TType > | Adds sparse `updates` to an existing tensor according to `indices`. |
| TensorScatterNdMax <T extends TType > | |
| TensorScatterNdMin <T extends TType > | |
| TensorScatterNdSub <T extends TType > | Subtracts sparse `updates` from an existing tensor according to `indices`. |
| TensorScatterNdUpdate <T extends TType > | Scatter `updates` into an existing tensor according to `indices`. |
| TensorShapeProto | Dimensions of a tensor. |
| TensorShapeProto.Builder | Dimensions of a tensor. |
| TensorShapeProto.Dim | One dimension of the tensor. |
| TensorShapeProto.Dim.Builder | One dimension of the tensor. |
| TensorShapeProto.DimOrBuilder | |
| TensorShapeProtoOrBuilder | |
| TensorShapeProtos | |
| TensorSliceDataset | |
| TensorSliceDataset | Creates a dataset that emits each dim-0 slice of `components` once. |
| TensorSliceProto | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Builder | Can only be interpreted if you know the corresponding TensorShape. |
| TensorSliceProto.Extent | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.Builder | Extent of the slice in one dimension. |
| TensorSliceProto.Extent.HasLengthCase | |
| TensorSliceProto.ExtentOrBuilder | |
| TensorSliceProtoOrBuilder | |
| TensorSliceProtos | |
| TensorSpecProto | A protobuf to represent tf.TensorSpec. |
| TensorSpecProto.Builder | A protobuf to represent tf.TensorSpec. |
| TensorSpecProtoOrBuilder | |
| TensorStridedSliceUpdate <T extends TType > | Assign `value` to the sliced l-value reference of `input`. |
| TensorStridedSliceUpdate.Options | Optional attributes for TensorStridedSliceUpdate |
| TensorSummary | Outputs a `Summary` protocol buffer with a tensor and per-plugin data. |
| TensorType | Annotation for all tensor types. |
| TensorTypeInfo <T extends TType > | Registered information about a tensor type. |
| TensorTypeRegistry | Repository of all registered tensor types. |
| TestLogProtos | |
| TestResults | The output of one benchmark / test run. |
| TestResults.BenchmarkType | The type of benchmark. |
| TestResults.Builder | The output of one benchmark / test run. |
| TestResultsOrBuilder | |
| TextLineDataset | |
| TextLineDataset | Creates a dataset that emits the lines of one or more text files. |
| TextLineReader | A Reader that outputs the lines of a file delimited by '\n'. |
| TextLineReader.Options | Optional attributes for TextLineReader |
| TF_AllocatorAttributes | |
| TF_ApiDefMap | |
| TF_AttrMetadata | |
| TF_Buffer | |
| TF_Buffer.Data_deallocator_Pointer_long | |
| TF_DeprecatedSession | |
| TF_DeviceList | |
| TF_DimensionHandle | |
| TF_Function | |
| TF_FunctionOptions | |
| TF_Graph | |
| TF_ImportGraphDefOptions | |
| TF_ImportGraphDefResults | |
| TF_Input | |
| TF_KernelBuilder | |
| TF_Library | |
| TF_OpDefinitionBuilder | |
| TF_Operation | |
| TF_OperationDescription | |
| TF_OpKernelConstruction | |
| TF_OpKernelContext | |
| TF_Output | |
| TF_Server | |
| TF_Session | |
| TF_SessionOptions | |
| TF_ShapeHandle | |
| TF_ShapeInferenceContext | |
| TF_Status | |
| TF_StringView | |
| TF_Tensor | |
| TF_TString | |
| TF_TString_Large | |
| TF_TString_Offset | |
| TF_TString_Raw | |
| TF_TString_Small | |
| TF_TString_Union | |
| TF_TString_View | |
| TF_WhileParams | |
| TFE_Context | |
| TFE_ContextOptions | |
| TFE_Op | |
| TFE_TensorDebugInfo | |
| TFE_TensorHandle | |
| TFFailedPreconditionException | |
| TFInvalidArgumentException | |
| TFloat16 | IEEE-754 half-precision 16-bit float tensor type. |
| TFloat16Mapper | Maps memory of DT_HALF tensors to a n-dimensional data space. |
| TFloat32 | IEEE-754 single-precision 32-bit float tensor type. |
| TFloat32Mapper | Maps memory of DT_FLOAT tensors to a n-dimensional data space. |
| TFloat64 | IEEE-754 double-precision 64-bit float tensor type. |
| TFloat64Mapper | Maps memory of DT_DOUBLE tensors to a n-dimensional data space. |
| TFloating | Common interface for all floating point tensors. |
| TFOutOfRangeException | |
| TFPermissionDeniedException | |
| TfRecordDataset | Creates a dataset that emits the records from one or more TFRecord files. |
| TFRecordDataset | |
| TfRecordReader | A Reader that outputs the records from a TensorFlow Records file. |
| TfRecordReader.Options | Optional attributes for TfRecordReader |
| TFResourceExhaustedException | |
| TFUnauthenticatedException | |
| TFUnimplementedException | |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolDataset | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle | Creates a dataset that uses a custom thread pool to compute `input_dataset`. |
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
| ThreadPoolHandle.Options | Optional attributes for ThreadPoolHandle |
| ThreadPoolOptionProto | Protobuf type tensorflow.ThreadPoolOptionProto |
| ThreadPoolOptionProto.Builder | Protobuf type tensorflow.ThreadPoolOptionProto |
| ThreadPoolOptionProtoOrBuilder | |
| Tile <T extends TType > | Constructs a tensor by tiling a given tensor. |
| TileGrad <T extends TType > | Returns the gradient of `Tile`. |
| Marca de tiempo | Provides the time since epoch in seconds. |
| TInt32 | 32-bit signed integer tensor type. |
| TInt32Mapper | Maps memory of DT_INT32 tensors to a n-dimensional data space. |
| TInt64 | 64-bit signed integer tensor type. |
| TInt64Mapper | Maps memory of DT_INT64 tensors to a n-dimensional data space. |
| TIntegral | Common interface for all integral numeric tensors. |
| Número TN | Common interface for all numeric tensors. |
| ToBool | Converts a tensor to a scalar predicate. |
| ToHashBucket | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketFast | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToHashBucketStrong | Converts each string in the input Tensor to its hash mod by a number of buckets. |
| ToNumber <T extends TNumber > | Converts each string in the input Tensor to the specified numeric type. |
| TopK <T extends TNumber > | Finds values and indices of the `k` largest elements for the last dimension. |
| TopK.Options | Optional attributes for TopK |
| TopKUnique | Returns the TopK unique values in the array in sorted order. |
| TopKWithUnique | Returns the TopK values in the array in sorted order. |
| TPUCompilationResult | Returns the result of a TPU compilation. |
| TPUEmbeddingActivations | An op enabling differentiation of TPU Embeddings. |
| TPUReplicatedInput <T extends TType > | Connects N inputs to an N-way replicated TPU computation. |
| TPUReplicatedInput.Options | Optional attributes for TPUReplicatedInput |
| TPUReplicatedOutput <T extends TType > | Connects N outputs from an N-way replicated TPU computation. |
| TPUReplicateMetadata | Metadata indicating how the TPU computation should be replicated. |
| TPUReplicateMetadata.Options | Optional attributes for TPUReplicateMetadata |
| TrackableObjectGraph | Protobuf type tensorflow.TrackableObjectGraph |
| TrackableObjectGraph.Builder | Protobuf type tensorflow.TrackableObjectGraph |
| TrackableObjectGraph.TrackableObject | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
| TrackableObjectGraph.TrackableObject.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject |
| TrackableObjectGraph.TrackableObject.ObjectReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
| TrackableObjectGraph.TrackableObject.ObjectReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference |
| TrackableObjectGraph.TrackableObject.ObjectReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObject.SerializedTensor | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
| TrackableObjectGraph.TrackableObject.SerializedTensor.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor |
| TrackableObjectGraph.TrackableObject.SerializedTensorOrBuilder | |
| TrackableObjectGraph.TrackableObject.SlotVariableReference | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
| TrackableObjectGraph.TrackableObject.SlotVariableReference.Builder | Protobuf type tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference |
| TrackableObjectGraph.TrackableObject.SlotVariableReferenceOrBuilder | |
| TrackableObjectGraph.TrackableObjectOrBuilder | |
| TrackableObjectGraphOrBuilder | |
| TrackableObjectGraphProtos | |
| TransportOptions | |
| TransportOptions.RecvBufRespExtra | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtra.Builder | Extra data needed on a non-RDMA RecvBufResponse. |
| TransportOptions.RecvBufRespExtraOrBuilder | |
| Transpose <T extends TType > | Shuffle dimensions of x according to a permutation. |
| TriangularSolve <T extends TType > | Solves systems of linear equations with upper or lower triangular matrices by backsubstitution. |
| TriangularSolve.Options | Optional attributes for TriangularSolve |
| TridiagonalMatMul <T extends TType > | Calculate product with tridiagonal matrix. |
| TridiagonalSolve <T extends TType > | Solves tridiagonal systems of equations. |
| TridiagonalSolve.Options | Optional attributes for TridiagonalSolve |
| TruncateDiv <T extends TType > | Returns x / y element-wise for integer types. |
| TruncatedNormal <T extends TFloating > | Initializer that generates a truncated normal distribution. |
| TruncatedNormal <U extends TNumber > | Outputs random values from a truncated normal distribution. |
| TruncatedNormal.Options | Optional attributes for TruncatedNormal |
| TruncateMod <T extends TNumber > | Returns element-wise remainder of division. |
| TryRpc | Perform batches of RPC requests. |
| TryRpc.Options | Optional attributes for TryRpc |
| TString | String type. |
| TStringInitializer <T> | Helper class for initializing a TString tensor. |
| TStringMapper | Maps memory of DT_STRING tensors to a n-dimensional data space. |
| TType | Common interface for all typed tensors. |
| TUint8 | 8-bit unsigned integer tensor type. |
| TUint8Mapper | Maps memory of DT_UINT8 tensors to a n-dimensional data space. |
| TupleValue | Represents a Python tuple. |
| TupleValue.Builder | Represents a Python tuple. |
| TupleValueOrBuilder | |
| TypeSpecProto | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
| TypeSpecProto.Builder | Represents a tf.TypeSpecProtobuf type tensorflow.TypeSpecProto |
| TypeSpecProto.TypeSpecClass | Protobuf enum tensorflow.TypeSpecProto.TypeSpecClass |
| TypeSpecProtoOrBuilder | |
| TypesProtos |
Ud.
| Unbatch <T extends TType > | Reverses the operation of Batch for a single output Tensor. |
| Unbatch.Options | Optional attributes for Unbatch |
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchDataset | A dataset that splits the elements of its input into multiple elements. |
| UnbatchGrad <T extends TType > | Gradient of Unbatch. |
| UnbatchGrad.Options | Optional attributes for UnbatchGrad |
| UncompressElement | Uncompresses a compressed dataset element. |
| UnicodeDecode <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecode.Options | Optional attributes for UnicodeDecode |
| UnicodeDecodeWithOffsets <T extends TNumber > | Decodes each string in `input` into a sequence of Unicode code points. |
| UnicodeDecodeWithOffsets.Options | Optional attributes for UnicodeDecodeWithOffsets |
| UnicodeEncode | Encode a tensor of ints into unicode strings. |
| UnicodeEncode.Options | Optional attributes for UnicodeEncode |
| UnicodeScript | Determine the script codes of a given tensor of Unicode integer code points. |
| UnicodeTranscode | Transcode the input text from a source encoding to a destination encoding. |
| UnicodeTranscode.Options | Optional attributes for UnicodeTranscode |
| UniformCandidateSampler | Generates labels for candidate sampling with a uniform distribution. |
| UniformCandidateSampler.Options | Optional attributes for UniformCandidateSampler |
| Unique <T extends TType , V extends TNumber > | Finds unique elements along an axis of a tensor. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueDataset | Creates a dataset that contains the unique elements of `input_dataset`. |
| UniqueWithCounts <T extends TType , V extends TNumber > | Finds unique elements along an axis of a tensor. |
| UnitNorm | Constrains the weights to have unit norm. |
| UnravelIndex <T extends TNumber > | Converts an array of flat indices into a tuple of coordinate arrays. |
| UnsortedSegmentJoin | Joins the elements of `inputs` based on `segment_ids`. |
| UnsortedSegmentJoin.Options | Optional attributes for UnsortedSegmentJoin |
| UnsortedSegmentMax <T extends TNumber > | Computes the maximum along segments of a tensor. |
| UnsortedSegmentMin <T extends TNumber > | Computes the minimum along segments of a tensor. |
| UnsortedSegmentProd <T extends TType > | Computes the product along segments of a tensor. |
| UnsortedSegmentSum <T extends TType > | Computes the sum along segments of a tensor. |
| Unstack <T extends TType > | Unpacks a given dimension of a rank-`R` tensor into `num` rank-`(R-1)` tensors. |
| Unstack.Options | Optional attributes for Unstack |
| Unstage | Op is similar to a lightweight Dequeue. |
| Unstage.Options | Optional attributes for Unstage |
| UnwrapDatasetVariant | |
| Superior | Converts all lowercase characters into their respective uppercase replacements. |
| Upper.Options | Optional attributes for Upper |
| UpperBound <U extends TNumber > | Applies upper_bound(sorted_search_values, values) along each row. |
V
| Validador | |
| Validador | |
| ValuesDef | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDef.Builder | Protocol buffer representing the values in ControlFlowContext. |
| ValuesDefOrBuilder | |
| VarHandleOp | Creates a handle to a Variable resource. |
| VarHandleOp.Options | Optional attributes for VarHandleOp |
| Variable <T extends TType > | Holds state in the form of a tensor that persists across steps. |
| Variable.Options | Optional attributes for Variable |
| VariableAggregation | Indicates how a distributed variable will be aggregated. |
| VariableDef | Protocol buffer representing a Variable. |
| VariableDef.Builder | Protocol buffer representing a Variable. |
| VariableDefOrBuilder | |
| VariableProtos | |
| VariableShape <T extends TNumber > | Returns the shape of the variable pointed to by `resource`. |
| VariableSynchronization | Indicates when a distributed variable will be synced. |
| VarianceScaling <T extends TFloating > | Initializer capable of adapting its scale to the shape of weights tensors. |
| VarianceScaling.Distribution | The random distribution to use when initializing the values. |
| VarianceScaling.Mode | The mode to use for calculating the fan values. |
| VariantTensorDataProto | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProto.Builder | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
| VariantTensorDataProtoOrBuilder | |
| VarIsInitializedOp | Checks whether a resource handle-based variable has been initialized. |
| VarLenFeatureProto | Protobuf type tensorflow.VarLenFeatureProto |
| VarLenFeatureProto.Builder | Protobuf type tensorflow.VarLenFeatureProto |
| VarLenFeatureProtoOrBuilder | |
| VerifierConfig | The config for graph verifiers. |
| VerifierConfig.Builder | The config for graph verifiers. |
| VerifierConfig.Toggle | Protobuf enum tensorflow.VerifierConfig.Toggle |
| VerifierConfigOrBuilder | |
| VerifierConfigProtos | |
| VersionDef | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDef.Builder | Version information for a piece of serialized data There are different types of versions for each type of data (GraphDef, etc.), but they all have the same common shape described here. |
| VersionDefOrBuilder | |
| VersionsProtos |
W.
| WatchdogConfig | Protobuf type tensorflow.WatchdogConfig |
| WatchdogConfig.Builder | Protobuf type tensorflow.WatchdogConfig |
| WatchdogConfigOrBuilder | |
| WeakPointerScope | A minimalist pointer scope only keeping weak references to its elements. |
| Dónde | Returns locations of nonzero / true values in a tensor. |
| WhileContextDef | Protocol buffer representing a WhileContext object. |
| WhileContextDef.Builder | Protocol buffer representing a WhileContext object. |
| WhileContextDefOrBuilder | |
| WholeFileReader | A Reader that outputs the entire contents of a file as a value. |
| WholeFileReader.Options | Optional attributes for WholeFileReader |
| WindowDataset | Combines (nests of) input elements into a dataset of (nests of) windows. |
| WorkerHealth | Current health status of a worker. |
| WorkerHeartbeat | Worker heartbeat op. |
| WorkerHeartbeatRequest | Protobuf type tensorflow.WorkerHeartbeatRequest |
| WorkerHeartbeatRequest.Builder | Protobuf type tensorflow.WorkerHeartbeatRequest |
| WorkerHeartbeatRequestOrBuilder | |
| WorkerHeartbeatResponse | Protobuf type tensorflow.WorkerHeartbeatResponse |
| WorkerHeartbeatResponse.Builder | Protobuf type tensorflow.WorkerHeartbeatResponse |
| WorkerHeartbeatResponseOrBuilder | |
| WorkerShutdownMode | Indicates the behavior of the worker when an internal error or shutdown signal is received. |
| WrapDatasetVariant | |
| WriteAudioSummary | Writes an audio summary. |
| WriteAudioSummary.Options | Optional attributes for WriteAudioSummary |
| WriteFile | Writes contents to the file at input filename. |
| WriteGraphSummary | Writes a graph summary. |
| WriteHistogramSummary | Writes a histogram summary. |
| WriteImageSummary | Writes an image summary. |
| WriteImageSummary.Options | Optional attributes for WriteImageSummary |
| WriteRawProtoSummary | Writes a serialized proto summary. |
| WriteScalarSummary | Writes a scalar summary. |
| WriteSummary | Writes a tensor summary. |
incógnita
| Xdivy <T extends TType > | Returns 0 if x == 0, and x / y otherwise, elementwise. |
| XEvento | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.Builder | An XEvent is a trace event, optionally annotated with XStats. |
| XEvent.DataCase | |
| XEventMetadata | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadata.Builder | Metadata for an XEvent, corresponds to an event type and is shared by all XEvents with the same metadata_id. |
| XEventMetadataOrBuilder | |
| XEventOrBuilder | |
| XlaRecvFromHost <T extends TType > | An op to receive a tensor from the host. |
| XlaSendToHost | An op to send a tensor to the host. |
| XlaSetBound | Set a bound for the given input value as a hint to Xla compiler, returns the same value. |
| XlaSpmdFullToShardShape <T extends TType > | An op used by XLA SPMD partitioner to switch from automatic partitioning to manual partitioning. |
| XlaSpmdShardToFullShape <T extends TType > | An op used by XLA SPMD partitioner to switch from manual partitioning to automatic partitioning. |
| XLine | An XLine is a timeline of trace events (XEvents). |
| XLine.Builder | An XLine is a timeline of trace events (XEvents). |
| XLineOrBuilder | |
| Xlog1py <T extends TType > | Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. |
| Xlogy <T extends TType > | Returns 0 if x == 0, and x * log(y) otherwise, elementwise. |
| XPlane | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlane.Builder | An XPlane is a container of parallel timelines (XLines), generated by a profiling source or by post-processing one or more XPlanes. |
| XPlaneOrBuilder | |
| XPlaneProtos | |
| XSpace | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpace.Builder | A container of parallel XPlanes, generated by one or more profiling sources. |
| XSpaceOrBuilder | |
| XStat | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.Builder | An XStat is a named value associated with an XEvent, e.g., a performance counter value, a metric computed by a formula applied over nested XEvents and XStats. |
| XStat.ValueCase | |
| XStatMetadata | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadata.Builder | Metadata for an XStat, corresponds to a stat type and is shared by all XStats with the same metadata_id. |
| XStatMetadataOrBuilder | |
| XStatOrBuilder |
z
| Zeros <T extends TType > | Creates an Initializer that sets all values to zero. |
| Zeros <T extends TType > | An operator creating a constant initialized with zeros of the shape given by `dims`. |
| ZerosLike <T extends TType > | Returns a tensor of zeros with the same shape and type as x. |
| Zeta <T extends TNumber > | Compute the Hurwitz zeta function \\(\zeta(x, q)\\). |
| ZipDataset | Creates a dataset that zips together `input_datasets`. |